https://doi.org/10.5281/zenodo.21403392

QSIRecon#

Reconstructing a structural connectome#

Author: Monika Doerig

Date: 16 July 2026

License:

Note: If this notebook uses neuroimaging tools from Neurocontainers, those tools retain their original licenses. Please see Neurodesk citation guidelines for details.

✨ Use of AI

This notebook was drafted with assistance from an LLM (GLM-5.2, via Neurodesk) and then revised by the author. The author reviewed the final content and takes responsibility for it.

Citation and Resources:#

Tools included in this workflow#

QSIRecon:

  • Cieslak, M., Cook, P. A., He, X., Yeh, F. C., Dhollander, T., Adebimpe, A., Aguirre, G. K., Bassett, D. S., Betzel, R. F., Bourque, J., Cabral, L. M., Davatzikos, C., Detre, J. A., Earl, E., Elliott, M. A., Fadnavis, S., Fair, D. A., Foran, W., Fotiadis, P., Garyfallidis, E., … Satterthwaite, T. D. (2021). QSIPrep: an integrative platform for preprocessing and reconstructing diffusion MRI data. Nature methods, 18(7), 775–778. https://doi.org/10.1038/s41592-021-01185-5

Workflows this work is based on#

Dataset#

OpenNeuro:

OSF Preprocessed data with QSIPrep :

  • Dörig, M. (2026, July 14). Diffusion MRI with QSIPrep & QSIRecon: Interactive NeurodeskEDU Examples. Retrieved from osf.io/q7v8c

Educational resources#

Load software tools and import python libraries#

# Load QSIRecon
import module
await module.load('qsirecon/1.1.0')
await module.list()
['qsirecon/1.1.0']

The base image already provides the common scientific Python packages (see the Neurodesktop Dockerfile). Only a few standard libraries are needed below.

# Import the necessary libraries
import os
import glob
import shutil
import numpy as np
import matplotlib.pyplot as plt
from pathlib import Path
from bs4 import BeautifulSoup
from IPython.display import HTML, display
import base64
import subprocess

FreeSurfer license#

# Request a freesurfer license from https://surfer.nmr.mgh.harvard.edu/registration.html
# and store it in your homedirectory 
# This is just an exampe - please replace with your license id:
!echo "Steffen.Bollmann@cai.uq.edu.au" > ~/.license
!echo "21029" >> ~/.license
!echo "*Cqyn12sqTCxo" >> ~/.license
!echo "FSxgcvGkNR59Y" >> ~/.license

Introduction#

QSIRecon is the post-processing companion to QSIPrep (it does for diffusion MRI what XCP-D does for BOLD). Where QSIPrep stops at preprocessed data, QSIRecon builds the workflows that turn it into many of the biologically interesting derivatives you actually test hypotheses on: ODF/FOD reconstruction, model fits and parameter estimates, tractography, tractometry, regional connectivity, and tabular outputs.

Its aim is to make state-of-the-art methods from DIPY, MRtrix3, DSI Studio, PyAFQ and other packages straightforward to apply to preprocessed dMRI. Rather than one fixed pipeline, QSIRecon offers a set of curated reconstruction workflows, selected at runtime.

This notebook runs one of them: an MRtrix3 multi-shell pipeline using MSMT-CSD to estimate fibre orientation distributions, iFOD2 probabilistic tractography to generate streamlines, and SIFT2 to weight them — producing a structural connectome, which we inspect in the QSIRecon visual report.

Learning objectives#

This notebook assumes a basic understanding of diffusion MRI and familiarity with QSIPrep’s role in preprocessing (see the companion QSIPrep notebook). By the end you will be able to:

  • Describe what QSIRecon does and how it relates to QSIPrep

  • Select and run a QSIRecon reconstruction workflow on QSIPrep derivatives

  • Inspect the resulting FOD, tractography and connectome outputs in the QSIRecon visual report

Data Preparation#

QSIRecon consumes QSIPrep derivatives. We download a copy of the output from the QSIPrep notebook from OSF, so this notebook can be run on its own.

def fetch_if_missing(remote, local):
    """Fetch from OSF, downloading to a temp name so a partial file never
    looks like a complete one on rerun."""
    if os.path.exists(local):
        print(f"Already exists, skipping download: {local}")
        return
    tmp = local + ".part"
    subprocess.run(["osf", "-p", "q7v8c", "fetch", remote, tmp], check=True)
    os.replace(tmp, local)
    print(f"Downloaded: {local}")

fetch_if_missing("qsiprep/qsiprep-CON01.tar.gz", "qsiprep-CON01.tar.gz")

if os.path.exists("qsiprep-output/sub-CON01"):
    print("Already extracted, skipping: qsiprep-output/sub-CON01")
else:
    os.makedirs("qsiprep-output", exist_ok=True)
    subprocess.run(["tar", "xzf", "qsiprep-CON01.tar.gz", "-C", "qsiprep-output"], check=True)
    print("Extracted QSIPrep derivatives to qsiprep-output/")

if os.path.exists("qsiprep-CON01.tar.gz"):
    os.remove("qsiprep-CON01.tar.gz")
    print("Removed tarball to save disk")
Downloaded: qsiprep-CON01.tar.gz
Extracted QSIPrep derivatives to qsiprep-output/
Removed tarball to save disk
  1%|▏         | 6.31M/453M [00:00<00:07, 58.4Mbytes/s]
  3%|▎         | 13.8M/453M [00:00<00:06, 67.7Mbytes/s]
  9%|▉         | 41.4M/453M [00:00<00:05, 76.6Mbytes/s]
 16%|█▌        | 70.9M/453M [00:00<00:03, 113Mbytes/s]
 27%|██▋       | 123M/453M [00:01<00:02, 152Mbytes/s]
 36%|███▌      | 162M/453M [00:01<00:01, 163Mbytes/s]
 45%|████▌     | 206M/453M [00:01<00:01, 189Mbytes/s]
 59%|█████▊    | 265M/453M [00:01<00:01, 183Mbytes/s]
 68%|██████▊   | 306M/453M [00:02<00:00, 158Mbytes/s]
 76%|███████▌  | 342M/453M [00:02<00:00, 163Mbytes/s]
 89%|████████▉ | 403M/453M [00:02<00:00, 174Mbytes/s]
100%|██████████| 453M/453M [00:02<00:00, 152Mbytes/s]

Analysis#

We run QSIRecon on the QSIPrep derivatives using the mrtrix_multishell_msmt_noACT reconstruction spec — an MRtrix3 multishell pipeline using MSMT-CSD for FOD estimation, iFOD2 probabilistic tractography, SIFT2 streamline weighting, and tck2connectome to produce a structural connectome.

As the name suggests, this spec does not use anatomically constrained tractography (ACT). The alternative mrtrix_multishell_msmt_ACT-hsvs spec constrains tractography using a hybrid surface-volume segmentation, but that requires FreeSurfer derivatives passed via --fs-subjects-dir, which our QSIPrep 1.0.1 run from the companion notebook doesn’t produce — FreeSurfer would have to be run separately. The mrtrix_multishell_msmt_ACT-fast variant substitutes FSL FAST for the segmentation, but the QSIRecon documentation does not recommend it. So we use the non-ACT spec here.

Customising the spec#

Reconstruction workflows are defined in YAML files, and --recon-spec accepts either a built-in name or a path to your own file. The built-in specs are a good starting point for customisation — so rather than invoking mrtrix_multishell_msmt_noACT by name, we download it and reduce tckgen’s select parameter from 10 million streamlines to 200,000.

This is purely to keep the notebook runnable in reasonable time and disk: streamline count drives most of the cost of tractography. A research analysis would use the full count. Note the YAML is fetched at a pinned commit (af43da9), which is the commit the QSIRecon version in this container was built from — so the spec we edit matches the built-in one.

Long-running

Even at a reduced streamline count, tractography plus SIFT2 is compute-heavy — expect this cell to take a while depending on available resources.

Let’s look at the command-line arguments first and then run qsirecon:

!qsirecon --help
usage: qsirecon [-h]
                [--participant-label PARTICIPANT_LABEL [PARTICIPANT_LABEL ...]]
                [--session-id SESSION_ID [SESSION_ID ...]]
                [-d PACKAGE=PATH [PACKAGE=PATH ...]] [--bids-filter-file FILE]
                [--bids-database-dir PATH] [--nprocs NPROCS]
                [--omp-nthreads OMP_NTHREADS] [--mem MEMORY_MB] [--low-mem]
                [--use-plugin FILE] [--sloppy] [--boilerplate-only]
                [--reports-only]
                [--report-output-level {root,subject,session}] [--infant]
                [--b0-threshold B0_THRESHOLD]
                [--output-resolution OUTPUT_RESOLUTION]
                [--fs-license-file PATH] [--recon-spec RECON_SPEC]
                [--input-type {qsiprep,ukb,hcpya}] [--fs-subjects-dir PATH]
                [--skip-odf-reports] [--atlases ATLAS [ATLAS ...]] [--version]
                [-v] [-w WORK_DIR] [--resource-monitor] [--config-file FILE]
                [--write-graph] [--stop-on-first-crash] [--notrack]
                [--debug {pdb,all} [{pdb,all} ...]]
                input_dir output_dir {participant}

QSIRecon v1.1.1.dev0+gaf43da9.d20250414: q-Space Image Reconstruction
Workflows

positional arguments:
  input_dir             The root folder of the input dataset (subject-level
                        folders should be found at the top level in this
                        folder). If the dataset is not BIDS-valid, then a
                        BIDS-compliant version will be created based on the
                        --input-type value.
  output_dir            The output path for the outcomes of postprocessing and
                        visual reports
  {participant}         Processing stage to be run, only "participant" in the
                        case of QSIRecon (for now).

options:
  -h, --help            show this help message and exit

Options for filtering input data:
  --participant-label PARTICIPANT_LABEL [PARTICIPANT_LABEL ...]
                        A space delimited list of participant identifiers or a
                        single identifier (the sub- prefix can be removed)
                        (default: None)
  --session-id SESSION_ID [SESSION_ID ...]
                        A space delimited list of session identifiers or a
                        single identifier (the ses- prefix can be removed)
                        (default: None)
  -d PACKAGE=PATH [PACKAGE=PATH ...], --datasets PACKAGE=PATH [PACKAGE=PATH ...]
                        Search PATH(s) for derivatives or atlas datasets.
                        These may be provided as named folders (e.g.,
                        ``--datasets smriprep=/path/to/smriprep``). (default:
                        None)
  --bids-filter-file FILE
                        A JSON file describing custom BIDS input filters using
                        PyBIDS. For further details, please check out https://
                        fmriprep.readthedocs.io/en/latest/faq.html#how-do-I-
                        select-only-certain-files-to-be-input-to-fMRIPrep
                        (default: None)
  --bids-database-dir PATH
                        Path to a PyBIDS database folder, for faster indexing
                        (especially useful for large datasets). Will be
                        created if not present. (default: None)

Options to handle performance:
  --nprocs NPROCS, --nthreads NPROCS, --n-cpus NPROCS
                        Maximum number of threads across all processes
                        (default: None)
  --omp-nthreads OMP_NTHREADS
                        Maximum number of threads per-process (default: None)
  --mem MEMORY_MB, --mem-mb MEMORY_MB
                        Upper bound memory limit for QSIRecon processes
                        (default: None)
  --low-mem             Attempt to reduce memory usage (will increase disk
                        usage in working directory) (default: False)
  --use-plugin FILE, --nipype-plugin-file FILE
                        Nipype plugin configuration file (default: None)
  --sloppy              Use low-quality tools for speed - TESTING ONLY
                        (default: False)

Options for performing only a subset of the workflow:
  --boilerplate-only, --boilerplate
                        Generate boilerplate only (default: False)
  --reports-only        Only generate reports, don't run workflows. This will
                        only rerun report aggregation, not reportlet
                        generation for specific nodes. (default: False)
  --report-output-level {root,subject,session}
                        Where should the html reports be written? By default
                        root will write them to the --output-dir. Other
                        options will write them into their subject or session
                        directory. (default: root)

Workflow configuration:
  --infant              configure pipelines to process infant brains (default:
                        False)
  --b0-threshold B0_THRESHOLD
                        any value in the .bval file less than this will be
                        considered a b=0 image. Current default threshold =
                        100; this threshold can be lowered or increased. Note,
                        setting this too high can result in inaccurate
                        results. (default: 100)
  --output-resolution OUTPUT_RESOLUTION
                        the isotropic voxel size in mm the data will be
                        resampled to after preprocessing. If set to a lower
                        value than the original voxel size, your data will be
                        upsampled using BSpline interpolation. (default: None)

Specific options for FreeSurfer preprocessing:
  --fs-license-file PATH
                        Path to FreeSurfer license key file. Get it (for free)
                        by registering at
                        https://surfer.nmr.mgh.harvard.edu/registration.html
                        (default: None)

Options for recon workflows:
  --recon-spec RECON_SPEC
                        json file specifying a reconstruction pipeline to be
                        run after preprocessing (default: None)
  --input-type {qsiprep,ukb,hcpya}
                        Specify which pipeline was used to create the data
                        specified as the input_dir.Not necessary to specify if
                        the data was processed by QSIPrep. Other options
                        include "ukb" for data processed with the UK BioBank
                        minimal preprocessing pipeline and "hcpya" for the HCP
                        young adult minimal preprocessing pipeline. (default:
                        qsiprep)
  --fs-subjects-dir PATH
                        Directory containing Freesurfer outputs to be
                        integrated into recon. Freesurfer must already be run.
                        QSIRecon will not run Freesurfer. (default: None)
  --skip-odf-reports    run only reconstruction, assumes preprocessing has
                        already completed. (default: False)

Parcellation options:
  --atlases ATLAS [ATLAS ...]
                        Selection of atlases to apply to the data. Built-in
                        atlases include: AAL116, AICHA384Ext,
                        Brainnetome246Ext, Gordon333Ext, and the 4S atlases.
                        (default: None)

Other options:
  --version             show program's version number and exit
  -v, --verbose         Increases log verbosity for each occurrence, debug
                        level is -vvv (default: 0)
  -w WORK_DIR, --work-dir WORK_DIR
                        Path where intermediate results should be stored
                        (default: /home/jovyan/workspace/books/examples/diffus
                        ion_imaging/work)
  --resource-monitor    Enable Nipype's resource monitoring to keep track of
                        memory and CPU usage (default: False)
  --config-file FILE    Use pre-generated configuration file. Values in file
                        will be overridden by command-line arguments.
                        (default: None)
  --write-graph         Write workflow graph. (default: False)
  --stop-on-first-crash
                        Force stopping on first crash, even if a work
                        directory was specified. (default: False)
  --notrack             Opt-out of sending tracking information of this run to
                        the QSIRecon developers. This information helps to
                        improve QSIRecon and provides an indicator of real
                        world usage crucial for obtaining funding. (default:
                        False)
  --debug {pdb,all} [{pdb,all} ...]
                        Debug mode(s) to enable. 'all' is alias for all
                        available modes. (default: None)

Now we’ll customise the spec file and reduce the streamlines to 20000:

%%bash
set -e -u -o pipefail

curl -fsSL -o recon_spec_ci.yaml \
  https://raw.githubusercontent.com/PennLINC/qsirecon/af43da9/qsirecon/data/pipelines/mrtrix_multishell_msmt_noACT.yaml

sed -i -E 's/^([[:space:]]*select:).*/\1 200000/' recon_spec_ci.yaml
grep -q 'select: 200000' recon_spec_ci.yaml || { echo "sed did not match — spec unchanged"; exit 1; }

cat recon_spec_ci.yaml
anatomical: []
name: mrtrix_multishell_msmt_noACT
nodes:
-   action: csd
    input: qsirecon
    nam
e: msmt_csd
    parameters:
        fod:
            algorithm: msmt_csd
            max_sh:
     - 8
            - 8
            - 8
        mtnormalize: true
        response:
            alg
orithm: dhollander
    qsirecon_suffix: MRtrix3_act-None
    software: MRTrix3
-   action: tractogra
phy
    input: msmt_csd
    name: track_ifod2
    parameters:
        sift2: {}
        tckgen:
        algorithm: iFOD2
            max_length: 250
            min_length: 30
            power: 0
.33
            quiet: true
            select: 200000
        use_5tt: false
        use_sift2: tru
e
    qsirecon_suffix: MRtrix3_act-None
    software: MRTrix3
-   action: connectivity
    input: tr
ack_ifod2
    name: mrtrix_conn
    parameters:
        tck2connectome:
        -   measure: sift_in
vnodevol_radius2_count
            scale_invnodevol: true
            search_radius: 2
            s
tat_edge: sum
            symmetric: true
            use_sift_weights: true
            zero_diagon
al: false
        -   length_scale: length
            measure: radius2_meanlength
            scale
_invnodevol: false
            search_radius: 2
            stat_edge: mean
            symmetric: t
rue
            use_sift_weights: false
            zero_diagonal: false
        -   measure: radius
2_count
            scale_invnodevol: false
            search_radius: 2
            stat_edge: sum
            symmetric: true
            use_sift_weights: false
            zero_diagonal: false
     -   measure: sift_radius2_count
            scale_invnodevol: false
            search_radius:
2
            stat_edge: sum
            symmetric: true
            use_sift_weights: true
    zero_diagonal: false
    qsirecon_suffix: MRtrix3_act-None
    software: MRTrix3
space: T1w
%%bash
set -e -u -o pipefail
# ensure subjects dir exists at startup
export SUBJECTS_DIR="$HOME/qsiprep-freesurfer-dir"
export APPTAINERENV_SUBJECTS_DIR=$SUBJECTS_DIR
export ITK_GLOBAL_DEFAULT_NUMBER_OF_THREADS=1
mkdir -p "$SUBJECTS_DIR"

N_CPUS=$(nproc); N_CPUS=$(( N_CPUS > 12 ? 12 : N_CPUS ))
MEM_MB=$(awk '/MemTotal/ {printf "%d", $2/1024}' /proc/meminfo)
QSIRECON_MEM=$(( MEM_MB * 75 / 100 ))
OMP_THREADS=$(( N_CPUS >= 8 ? 4 : 2 ))

qsirecon qsiprep-output qsirecon-output participant \
    --participant-label CON01 \
    --recon-spec recon_spec_ci.yaml \
    --fs-license-file ~/.license \
    --atlases AAL116 \
    -w qsirecon-work \
    --nthreads "${N_CPUS}" --omp-nthreads "${OMP_THREADS}" --mem-mb "${QSIRECON_MEM}" \
    2>&1 | tee qsirecon.log
260717-00:50:59,864 nipype.workflow IMPORTANT:
	 Running QSIRecon version 1.1.1.dev0+gaf43da9.d20250
414

         License NOTICE ##################################################
         QSIRecon 1.
1.1.dev0+gaf43da9.d20250414
         Copyright The PennLINC Developers.
         
         This prod
uct includes software developed by
         the NiPreps Community (https://nipreps.org/).
         Portions of this software were developed at the Department of
         Psychology at Stanfo
rd University, Stanford, CA, US.
         
         This software is also distributed as a Docker co
ntainer image.
         The bootstrapping file for the image ("Dockerfile") is licensed
         und
er the MIT License.
         
         This software may be distributed through an add-on package ca
lled
         "Docker Wrapper" that is under the BSD 3-clause License.
         ####################
#############################################
260717-00:51:00,30 nipype.workflow IMPORTANT:
	 Building QSIRecon's workflow:
           * BIDS data
set path: /home/jovyan/workspace/books/examples/diffusion_imaging/qsiprep-output.
           * Parti
cipant list: ['CON01'].
           * Run identifier: 20260717-005045_82fbfcfd-1246-4f9c-b202-3760041
c1194.
260717-00:51:02,685 nipype.utils INFO:
	 Collected anatomical data:
acpc_aparc: null
acpc_aseg: /hom
e/jovyan/workspace/books/examples/diffusion_imaging/qsiprep-output/sub-CON01/anat/sub-CON01_space-AC
PC_desc-aseg_dseg.nii.gz
acpc_brain_mask: /home/jovyan/workspace/books/examples/diffusion_imaging/qs
iprep-output/sub-CON01/anat/sub-CON01_space-ACPC_desc-brain_mask.nii.gz
acpc_csf_probseg: null
acpc_
gm_probseg: null
acpc_preproc: /home/jovyan/workspace/books/examples/diffusion_imaging/qsiprep-outpu
t/sub-CON01/anat/sub-CON01_space-ACPC_desc-preproc_T1w.nii.gz
acpc_seg: /home/jovyan/workspace/books
/examples/diffusion_imaging/qsiprep-output/sub-CON01/anat/sub-CON01_space-ACPC_dseg.nii.gz
acpc_to_t
emplate_xfm: /home/jovyan/workspace/books/examples/diffusion_imaging/qsiprep-output/sub-CON01/anat/s
ub-CON01_from-ACPC_to-MNI152NLin2009cAsym_mode-image_xfm.h5
acpc_wm_probseg: null
orig_to_acpc_xfm:
null
template_to_acpc_xfm: /home/jovyan/workspace/books/examples/diffusion_imaging/qsiprep-output/su
b-CON01/anat/sub-CON01_from-MNI152NLin2009cAsym_to-ACPC_mode-image_xfm.h5
260717-00:51:02,686 nipype.workflow INFO:
	 Anatomical data available for /home/jovyan/workspace/boo
ks/examples/diffusion_imaging/qsiprep-output/sub-CON01/anat/sub-CON01_space-ACPC_desc-preproc_T1w.ni
i.gz:
acpc_aparc: null
acpc_aseg: /home/jovyan/workspace/books/examples/diffusion_imaging/qsiprep-ou
tput/sub-CON01/anat/sub-CON01_space-ACPC_desc-aseg_dseg.nii.gz
acpc_brain_mask: /home/jovyan/workspa
ce/books/examples/diffusion_imaging/qsiprep-output/sub-CON01/anat/sub-CON01_space-ACPC_desc-brain_ma
sk.nii.gz
acpc_csf_probseg: null
acpc_gm_probseg: null
acpc_preproc: /home/jovyan/workspace/books/ex
amples/diffusion_imaging/qsiprep-output/sub-CON01/anat/sub-CON01_space-ACPC_desc-preproc_T1w.nii.gz
acpc_seg: /home/jovyan/workspace/books/examples/diffusion_imaging/qsiprep-output/sub-CON01/anat/sub-
CON01_space-ACPC_dseg.nii.gz
acpc_to_template_xfm: /home/jovyan/workspace/books/examples/diffusion_i
maging/qsiprep-output/sub-CON01/anat/sub-CON01_from-ACPC_to-MNI152NLin2009cAsym_mode-image_xfm.h5
ac
pc_wm_probseg: null
orig_to_acpc_xfm: null
template_to_acpc_xfm: /home/jovyan/workspace/books/exampl
es/diffusion_imaging/qsiprep-output/sub-CON01/anat/sub-CON01_from-MNI152NLin2009cAsym_to-ACPC_mode-i
mage_xfm.h5

260717-00:51:02,688 nipype.workflow INFO:
	 Found high-res anatomical data in preproces
sed inputs for CON01.
260717-00:51:02,688 nipype.workflow INFO:
	 acpc_aparc (<class 'str'>): None (
<class 'NoneType'>)
260717-00:51:02,688 nipype.workflow INFO:
	 acpc_seg (<class 'str'>): /home/jovy
an/workspace/books/examples/diffusion_imaging/qsiprep-output/sub-CON01/anat/sub-CON01_space-ACPC_dse
g.nii.gz (<class 'str'>)
260717-00:51:02,688 nipype.workflow INFO:
	 acpc_aseg (<class 'str'>): /hom
e/jovyan/workspace/books/examples/diffusion_imaging/qsiprep-output/sub-CON01/anat/sub-CON01_space-AC
PC_desc-aseg_dseg.nii.gz (<class 'str'>)
260717-00:51:02,689 nipype.workflow INFO:
	 acpc_brain_mask
 (<class 'str'>): /home/jovyan/workspace/books/examples/diffusion_imaging/qsiprep-output/sub-CON01/a
nat/sub-CON01_space-ACPC_desc-brain_mask.nii.gz (<class 'str'>)
260717-00:51:02,689 nipype.workflow
INFO:
	 acpc_preproc (<class 'str'>): /home/jovyan/workspace/books/examples/diffusion_imaging/qsipre
p-output/sub-CON01/anat/sub-CON01_space-ACPC_desc-preproc_T1w.nii.gz (<class 'str'>)
260717-00:51:02,689 nipype.workflow INFO:
	 acpc_csf_probseg (<class 'str'>): None (<class 'NoneType
'>)
260717-00:51:02,689 nipype.workflow INFO:
	 acpc_gm_probseg (<class 'str'>): None (<class 'NoneT
ype'>)
260717-00:51:02,689 nipype.workflow INFO:
	 acpc_wm_probseg (<class 'str'>): None (<class 'No
neType'>)
260717-00:51:02,689 nipype.workflow INFO:
	 orig_to_acpc_xfm (<class 'str'>): None (<class
 'NoneType'>)
260717-00:51:02,689 nipype.workflow INFO:
	 template_to_acpc_xfm (<class 'str'>): /hom
e/jovyan/workspace/books/examples/diffusion_imaging/qsiprep-output/sub-CON01/anat/sub-CON01_from-MNI
152NLin2009cAsym_to-ACPC_mode-image_xfm.h5 (<class 'str'>)
260717-00:51:02,689 nipype.workflow INFO:

	 acpc_to_template_xfm (<class 'str'>): /home/jovyan/workspace/books/examples/diffusion_imaging/qsi
prep-output/sub-CON01/anat/sub-CON01_from-ACPC_to-MNI152NLin2009cAsym_mode-image_xfm.h5 (<class 'str
'>)
260717-00:51:02,761 nipype.workflow INFO:
	 Found 1 high-res anatomicals to process
260717-00:51:02,767 nipype.workflow INFO:
	 Found T1w-to-template transforms from QSIRecon
260717-00:51:02,767 nipype.workflow INFO:
	 Transforming ODF ROIs into DWI space for visual report.
260717-00:51:02,778 nipype.interface INFO:
	 Response configuration: {'algorithm': 'dhollander', 'nt
hreads': 4}
260717-00:51:02,778 nipype.interface INFO:
	 Using 4 threads in MRtrix3
260717-00:51:06,83 nipype.workflow INFO:
	 QSIRecon workflow graph with 65 nodes built successfully.
260717-00:51:21,466 nipype.workflow IMPORTANT:
	 QSIRecon started!
260717-00:51:26,556 nipype.workflow INFO:
	 [Node] Setting-up "qsirecon_1_1_wf.sub-CON01_mrtrix_mult
ishell_msmt_noACT.datasink_atlas_orig_AAL116_0" in "/home/jovyan/workspace/books/examples/diffusion_
imaging/qsirecon-work/qsirecon_1_1_wf/sub-CON01_mrtrix_multishell_msmt_noACT/datasink_atlas_orig_AAL
116_0".
260717-00:51:26,558 nipype.workflow INFO:
	 [Node] Executing "datasink_atlas_orig_AAL116_0" <qsireco
n.interfaces.bids.CopyAtlas>
260717-00:51:26,563 nipype.workflow INFO:
	 [Node] Finished "datasink_atlas_orig_AAL116_0", elapsed
time 0.002405s.
260717-00:51:26,616 nipype.workflow INFO:
	 [Node] Setting-up "qsirecon_1_1_wf.sub-CON01_mrtrix_mult
ishell_msmt_noACT.datasink_atlas_labels_orig_AAL116_0" in "/home/jovyan/workspace/books/examples/dif
fusion_imaging/qsirecon-work/qsirecon_1_1_wf/sub-CON01_mrtrix_multishell_msmt_noACT/datasink_atlas_l
abels_orig_AAL116_0".
260717-00:51:26,618 nipype.workflow INFO:
	 [Node] Executing "datasink_atlas_labels_orig_AAL116_0" <
qsirecon.interfaces.bids.CopyAtlas>
260717-00:51:26,621 nipype.workflow INFO:
	 [Node] Finished "datasink_atlas_labels_orig_AAL116_0", e
lapsed time 0.000426s.
260717-00:51:26,696 nipype.workflow INFO:
	 [Node] Setting-up "qsirecon_1_1_wf.sub-CON01_mrtrix_mult
ishell_msmt_noACT.sub_CON01_ses_preop_acq_AP_space_ACPC_desc_preproc_ingressed_dwi_data" in "/home/j
ovyan/workspace/books/examples/diffusion_imaging/qsirecon-work/qsirecon_1_1_wf/sub-CON01_mrtrix_mult
ishell_msmt_noACT/sub_CON01_ses_preop_acq_AP_space_ACPC_desc_preproc_ingressed_dwi_data".
260717-00:51:26,698 nipype.workflow INFO:
	 [Node] Executing "sub_CON01_ses_preop_acq_AP_space_ACPC_
desc_preproc_ingressed_dwi_data" <qsirecon.interfaces.ingress.QSIPrepDWIIngress>
260717-00:51:26,703 nipype.workflow INFO:
	 [Node] Finished "sub_CON01_ses_preop_acq_AP_space_ACPC_d
esc_preproc_ingressed_dwi_data", elapsed time 0.002105s.
260717-00:51:26,838 nipype.workflow INFO:
	 [Node] Setting-up "qsirecon_1_1_wf.sub-CON01_mrtrix_mult
ishell_msmt_noACT.sub_CON01_ses_preop_acq_AP_space_ACPC_desc_preproc_dwi_specific_anat_wf.get_templa
te" in "/home/jovyan/workspace/books/examples/diffusion_imaging/qsirecon-work/qsirecon_1_1_wf/sub-CO
N01_mrtrix_multishell_msmt_noACT/sub_CON01_ses_preop_acq_AP_space_ACPC_desc_preproc_dwi_specific_ana
t_wf/get_template".
260717-00:51:26,840 nipype.workflow INFO:
	 [Node] Executing "get_template" <qsirecon.interfaces.ana
tomical.GetTemplate>
Downloading https://templateflow.s3.amazonaws.com/tpl-MNI152NLin2009cAsym/tpl-MNI152NLin2009cAsym_re
s-01_T1w.nii.gz
  0%|          | 0.00/13.7M [00:00<?, ?B/s]
260717-00:51:27,715 nipype.workflow INFO:
	 [Node] Setting-up "qsirecon_1_1_wf.sub-CON01_mrtrix_mult
ishell_msmt_noACT.sub_CON01_ses_preop_acq_AP_space_ACPC_desc_preproc_dwi_specific_anat_wf.resample_m
ask" in "/home/jovyan/workspace/books/examples/diffusion_imaging/qsirecon-work/qsirecon_1_1_wf/sub-C
ON01_mrtrix_multishell_msmt_noACT/sub_CON01_ses_preop_acq_AP_space_ACPC_desc_preproc_dwi_specific_an
at_wf/resample_mask".
260717-00:51:27,716 nipype.workflow INFO:
	 [Node] Setting-up "qsirecon_1_1_wf.sub-CON01_mrtrix_mult
ishell_msmt_noACT.sub_CON01_ses_preop_acq_AP_space_ACPC_desc_preproc_dwi_specific_anat_wf.odf_rois"
in "/home/jovyan/workspace/books/examples/diffusion_imaging/qsirecon-work/qsirecon_1_1_wf/sub-CON01_
mrtrix_multishell_msmt_noACT/sub_CON01_ses_preop_acq_AP_space_ACPC_desc_preproc_dwi_specific_anat_wf
/odf_rois".
260717-00:51:27,719 nipype.workflow INFO:
	 [Node] Executing "resample_mask" <nipype.interfaces.ants
.resampling.ApplyTransforms>
260717-00:51:27,720 nipype.workflow INFO:
	 [Node] Executing "odf_rois" <nipype.interfaces.ants.resa
mpling.ApplyTransforms>
  0%|          | 17.4k/13.7M [00:00<02:38, 86.4kB/s]
  0%|          | 52.2k/13.7M [00:00<01:38, 138kB/s]
260717-00:51:28,213 nipype.workflow INFO:
	 [Node] Finished "resample_mask", elapsed time 0.278392s.
  1%|          | 157k/13.7M [00:00<00:43, 312kB/s]
  2%|▏         | 331k/13.7M [00:00<00:25, 530kB/s]
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 11%|█         | 1.44M/13.7M [00:01<00:06, 1.91MB/s]
 21%|██▏       | 2.93M/13.7M [00:01<00:02, 3.69MB/s]
 43%|████▎     | 5.90M/13.7M [00:01<00:01, 7.19MB/s]
 66%|██████▌   | 8.99M/13.7M [00:01<00:00, 9.72MB/s]
 92%|█████████▏| 12.6M/13.7M [00:02<00:00, 12.2MB/s]
100%|██████████| 13.7M/13.7M [00:02<00:00, 6.63MB/s]
Downloading https://templateflow.s3.amazonaws.com/tpl-MNI152NLin2009cAsym/tpl-MNI152NLin2009cAsym_re
s-01_desc-brain_mask.nii.gz
  0%|          | 0.00/160k [00:00<?, ?B/s]
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100%|██████████| 160k/160k [00:00<00:00, 263kB/s]
260717-00:51:30,963 nipype.workflow INFO:
	 [Node] Finished "get_template", elapsed time 4.120073s.
260717-00:51:34,121 nipype.workflow INFO:
	 [Node] Finished "odf_rois", elapsed time 6.181527s.
labelconvert: Image "/home/jovyan/workspace/books/examples/diffusion_imaging/qsirecon-work/qsirecon_
1_1_wf/sub-CON01_mrtrix_multishell_msmt_noACT/sub_CON01_ses_preop_acq_AP_space_ACPC_desc_preproc_dwi
_specific_anat_wf/prepare_atlases/atlas-AAL116_space-MNI152NLin2009cAsym_res-01_dseg_to_dwi.nii.gz"
stored with floating-point type; need to check for non-integer or negative values
labelconvert: [ 10%] uncompressing image "/home/jovyan/workspace/books/examples/diffusion_imag
ing/qsirecon-work/qsirecon_1_1_wf/sub-CON01_mrtrix_multishell_msmt_noACT/sub_CON01_ses_preop_acq_AP_
space_ACPC_desc_preproc_dwi_specific_anat_wf/prepare_atlases/atlas-AAL116_space-MNI152NLin2009cAsym_
res-01_dseg_to_dwi.nii.gz"...?7h
labelconvert: [ 20%] uncompressing image "/home/jovyan/workspace/books/examples/diffusion_imag
ing/qsirecon-work/qsirecon_1_1_wf/sub-CON01_mrtrix_multishell_msmt_noACT/sub_CON01_ses_preop_acq_AP_
space_ACPC_desc_preproc_dwi_specific_anat_wf/prepare_atlases/atlas-AAL116_space-MNI152NLin2009cAsym_
res-01_dseg_to_dwi.nii.gz"...?7h
labelconvert: [ 30%] uncompressing image "/home/jovyan/workspace/books/examples/diffusion_imag
ing/qsirecon-work/qsirecon_1_1_wf/sub-CON01_mrtrix_multishell_msmt_noACT/sub_CON01_ses_preop_acq_AP_
space_ACPC_desc_preproc_dwi_specific_anat_wf/prepare_atlases/atlas-AAL116_space-MNI152NLin2009cAsym_
res-01_dseg_to_dwi.nii.gz"...?7h
labelconvert: [ 40%] uncompressing image "/home/jovyan/workspace/books/examples/diffusion_imag
ing/qsirecon-work/qsirecon_1_1_wf/sub-CON01_mrtrix_multishell_msmt_noACT/sub_CON01_ses_preop_acq_AP_
space_ACPC_desc_preproc_dwi_specific_anat_wf/prepare_atlases/atlas-AAL116_space-MNI152NLin2009cAsym_
res-01_dseg_to_dwi.nii.gz"...?7h
labelconvert: [ 50%] uncompressing image "/home/jovyan/workspace/books/examples/diffusion_imag
ing/qsirecon-work/qsirecon_1_1_wf/sub-CON01_mrtrix_multishell_msmt_noACT/sub_CON01_ses_preop_acq_AP_
space_ACPC_desc_preproc_dwi_specific_anat_wf/prepare_atlases/atlas-AAL116_space-MNI152NLin2009cAsym_
res-01_dseg_to_dwi.nii.gz"...?7h
labelconvert: [ 60%] uncompressing image "/home/jovyan/workspace/books/examples/diffusion_imag
ing/qsirecon-work/qsirecon_1_1_wf/sub-CON01_mrtrix_multishell_msmt_noACT/sub_CON01_ses_preop_acq_AP_
space_ACPC_desc_preproc_dwi_specific_anat_wf/prepare_atlases/atlas-AAL116_space-MNI152NLin2009cAsym_
res-01_dseg_to_dwi.nii.gz"...?7h
labelconvert: [ 70%] uncompressing image "/home/jovyan/workspace/books/examples/diffusion_imag
ing/qsirecon-work/qsirecon_1_1_wf/sub-CON01_mrtrix_multishell_msmt_noACT/sub_CON01_ses_preop_acq_AP_
space_ACPC_desc_preproc_dwi_specific_anat_wf/prepare_atlases/atlas-AAL116_space-MNI152NLin2009cAsym_
res-01_dseg_to_dwi.nii.gz"...?7h
labelconvert: [ 80%] uncompressing image "/home/jovyan/workspace/books/examples/diffusion_imag
ing/qsirecon-work/qsirecon_1_1_wf/sub-CON01_mrtrix_multishell_msmt_noACT/sub_CON01_ses_preop_acq_AP_
space_ACPC_desc_preproc_dwi_specific_anat_wf/prepare_atlases/atlas-AAL116_space-MNI152NLin2009cAsym_
res-01_dseg_to_dwi.nii.gz"...?7h
labelconvert: [ 90%] uncompressing image "/home/jovyan/workspace/books/examples/diffusion_imag
ing/qsirecon-work/qsirecon_1_1_wf/sub-CON01_mrtrix_multishell_msmt_noACT/sub_CON01_ses_preop_acq_AP_
space_ACPC_desc_preproc_dwi_specific_anat_wf/prepare_atlases/atlas-AAL116_space-MNI152NLin2009cAsym_
res-01_dseg_to_dwi.nii.gz"...?7h
labelconvert: [100%] uncompressing image "/home/jovyan/workspace/books/examples/diffusion_imag
ing/qsirecon-work/qsirecon_1_1_wf/sub-CON01_mrtrix_multishell_msmt_noACT/sub_CON01_ses_preop_acq_AP_
space_ACPC_desc_preproc_dwi_specific_anat_wf/prepare_atlases/atlas-AAL116_space-MNI152NLin2009cAsym_
res-01_dseg_to_dwi.nii.gz"...?7h
labelconvert: [100%] uncompressing image "/home/jovyan/workspace/books/examples/diffusion_imaging/q
sirecon-work/qsirecon_1_1_wf/sub-CON01_mrtrix_multishell_msmt_noACT/sub_CON01_ses_preop_acq_AP_space
_ACPC_desc_preproc_dwi_specific_anat_wf/prepare_atlases/atlas-AAL116_space-MNI152NLin2009cAsym_res-0
1_dseg_to_dwi.nii.gz"
l
labelconvert: [  2%] Verifying par
labelconvert: [  3%] Verifying parcellation image...?7h?7l
labelconvert: [  5%] Verifying pa
labelconvert: [  6%] Verifying parcellation image...?7h
labelconvert: [  8%] Verify
labelconvert: [  9%] Verifying parcellation image...?7
labelconvert: [ 11%] Verif
labelconvert: [ 12%] Verifying parcellation image...?
labelconvert: [ 14%] Veri
labelconvert: [ 15%] Verifying parcellation image...
labelconvert: [ 17%] Ver
labelconvert: [ 18%] Verifying parcellation image...
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labelconvert: [ 21%] Verifying parcellation image...
labelconvert: [ 23%] V
labelconvert: [ 24%] Verifying parcellation image...0
labelconvert: [ 26%]
labelconvert: [ 27%] Verifying parcellation image...
0K?7h
labelconvert: [ 29%] Verify
labelconvert: [ 30%] Verifying parcellation image...?7
labelconvert: [ 32%] Verif
labelconvert: [ 33%] Verifying parcellation image...?
labelconvert: [ 35%] Veri
labelconvert: [ 36%] Verifying parcellation image...
labelconvert: [ 38%] Ver
labelconvert: [ 39%] Verifying parcellation image...
labelconvert: [ 41%] Ve
labelconvert: [ 42%] Verifying parcellation image...
labelconvert: [ 44%] V
labelconvert: [ 45%] Verifying parcellation image...0
labelconvert: [ 47%]
labelconvert: [ 48%] Verifying parcellation image...
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labelconvert: [ 51%] Verifying parcellation image...
labelconvert: [ 53%
labelconvert: [ 54%] Verifying parcellation image...
labelconvert: [ 56
labelconvert: [ 57%] Verifying parcellation image..
labelconvert: [ 5
labelconvert: [ 60%] Verifying parcellation image.
labelconvert: [
labelconvert: [ 63%] Verifying parcellation image
labelconvert: [
 65%] Verifying parcellation image...?7h
labelconvert: [ 67%] Verify
labelconvert: [ 68%] Verifying parcellation image...?7
labelconvert: [ 70%] Verif
labelconvert: [ 71%] Verifying parcellation image...?
labelconvert: [ 73%] Veri
labelconvert: [ 74%] Verifying parcellation image...
labelconvert: [ 76%] Ver
labelconvert: [ 77%] Verifying parcellation image...
labelconvert: [ 79%] Ve
labelconvert: [ 80%] Verifying parcellation image...
labelconvert: [ 82%] V
labelconvert: [ 83%] Verifying parcellation image...0
labelconvert: [ 85%]
labelconvert: [ 86%] Verifying parcellation image...
labelconvert: [ 88%]
labelconvert: [ 89%] Verifying parcellation image...
labelconvert: [ 91%
labelconvert: [ 92%] Verifying parcellation image...
labelconvert: [ 94
labelconvert: [ 95%] Verifying parcellation image..
labelconvert: [ 9
labelconvert: [ 98%] Verifying parcellation image.
labelconvert: [1
labelconvert: [100%] Verifying parcellation image
labelconvert: [ 10%] uncompressing image "/home/jovyan/workspace/books/examples/diffusion_imag
ing/qsirecon-work/qsirecon_1_1_wf/sub-CON01_mrtrix_multishell_msmt_noACT/sub_CON01_ses_preop_acq_AP_
space_ACPC_desc_preproc_dwi_specific_anat_wf/prepare_atlases/atlas-AAL116_space-MNI152NLin2009cAsym_
res-01_dseg_to_dwi.nii.gz"...?7h
labelconvert: [ 20%] uncompressing image "/home/jovyan/workspace/books/examples/diffusion_imag
ing/qsirecon-work/qsirecon_1_1_wf/sub-CON01_mrtrix_multishell_msmt_noACT/sub_CON01_ses_preop_acq_AP_
space_ACPC_desc_preproc_dwi_specific_anat_wf/prepare_atlases/atlas-AAL116_space-MNI152NLin2009cAsym_
labelconvert: [ 30%] uncompressing image "/home/jovyan/w
orkspace/books/examples/diffusion_imaging/qsirecon-work/qsirecon_1_1_wf/sub-CON01_mrtrix_multishell_
msmt_noACT/sub_CON01_ses_preop_acq_AP_space_ACPC_desc_preproc_dwi_specific_anat_wf/prepare_atlases/a
labelconvert: [ 40
%] uncompressing image "/home/jovyan/workspace/books/examples/diffusion_imaging/qsirecon-work/qsirec
on_1_1_wf/sub-CON01_mrtrix_multishell_msmt_noACT/sub_CON01_ses_preop_acq_AP_space_ACPC_desc_preproc_
dwi_specific_anat_wf/prepare_atlases/atlas-AAL116_space-MNI152NLin2009cAsym_res-01_dseg_to_dwi.nii.g
labelconvert: [ 50%] uncompressing image "/home/jovyan/workspace/books/examples/
diffusion_imaging/qsirecon-work/qsirecon_1_1_wf/sub-CON01_mrtrix_multishell_msmt_noACT/sub_CON01_ses
_preop_acq_AP_space_ACPC_desc_preproc_dwi_specific_anat_wf/prepare_atlases/atlas-AAL116_space-MNI152
labelconvert: [ 60%] uncompressing image "
/home/jovyan/workspace/books/examples/diffusion_imaging/qsirecon-work/qsirecon_1_1_wf/sub-CON01_mrtr
ix_multishell_msmt_noACT/sub_CON01_ses_preop_acq_AP_space_ACPC_desc_preproc_dwi_specific_anat_wf/pre
labe
lconvert: [ 70%] uncompressing image "/home/jovyan/workspace/books/examples/diffusion_imaging/qsirec
on-work/qsirecon_1_1_wf/sub-CON01_mrtrix_multishell_msmt_noACT/sub_CON01_ses_preop_acq_AP_space_ACPC
_desc_preproc_dwi_specific_anat_wf/prepare_atlases/atlas-AAL116_space-MNI152NLin2009cAsym_res-01_dse
labelconvert: [ 80%] uncompressing image "/home/jovyan/workspace/b
ooks/examples/diffusion_imaging/qsirecon-work/qsirecon_1_1_wf/sub-CON01_mrtrix_multishell_msmt_noACT
/sub_CON01_ses_preop_acq_AP_space_ACPC_desc_preproc_dwi_specific_anat_wf/prepare_atlases/atlas-AAL11
6_space-MNI152NLin2009cAsym_res-01_dseg_to_dwi.nii.gz"...?7h
labelconvert: [ 90%] uncompressing image "/home/jovyan/workspace/books/examples/diffusion_imag
ing/qsirecon-work/qsirecon_1_1_wf/sub-CON01_mrtrix_multishell_msmt_noACT/sub_CON01_ses_preop_acq_AP_
space_ACPC_desc_preproc_dwi_specific_anat_wf/prepare_atlases/atlas-AAL116_space-MNI152NLin2009cAsym_
labelconvert: [100%] uncompressing image "/home/jovyan/w
orkspace/books/examples/diffusion_imaging/qsirecon-work/qsirecon_1_1_wf/sub-CON01_mrtrix_multishell_
msmt_noACT/sub_CON01_ses_preop_acq_AP_space_ACPC_desc_preproc_dwi_specific_anat_wf/prepare_atlases/a
labelconvert: [100%] un
compressing image "/home/jovyan/workspace/books/examples/diffusion_imaging/qsirecon-work/qsirecon_1_
1_wf/sub-CON01_mrtrix_multishell_msmt_noACT/sub_CON01_ses_preop_acq_AP_space_ACPC_desc_preproc_dwi_s
pecific_anat_wf/prepare_atlases/atlas-AAL116_space-MNI152NLin2009cAsym_res-01_dseg_to_dwi.nii.gz"0
K
260717-00:51:35,7 nipype.workflow INFO:
	 [Node] Setting-up "qsirecon_1_1_wf.sub-CON01_mrtrix_multis
hell_msmt_noACT.sub_CON01_ses_preop_acq_AP_space_ACPC_desc_preproc_dwi_specific_anat_wf.output_grid_
wf.voxel_size_chooser" in "/home/jovyan/workspace/books/examples/diffusion_imaging/qsirecon-work/qsi
recon_1_1_wf/sub-CON01_mrtrix_multishell_msmt_noACT/sub_CON01_ses_preop_acq_AP_space_ACPC_desc_prepr
oc_dwi_specific_anat_wf/output_grid_wf/voxel_size_chooser".
260717-00:51:35,12 nipype.workflow INFO:
	 [Node] Executing "voxel_size_chooser" <qsirecon.interface
s.anatomical.VoxelSizeChooser>
260717-00:51:35,37 nipype.workflow INFO:
	 [Node] Setting-up "qsirecon_1_1_wf.sub-CON01_mrtrix_multi
shell_msmt_noACT.sub_CON01_ses_preop_acq_AP_space_ACPC_desc_preproc_dwi_specific_anat_wf.mask_templa
te" in "/home/jovyan/workspace/books/examples/diffusion_imaging/qsirecon-work/qsirecon_1_1_wf/sub-CO
N01_mrtrix_multishell_msmt_noACT/sub_CON01_ses_preop_acq_AP_space_ACPC_desc_preproc_dwi_specific_ana
t_wf/mask_template".
260717-00:51:35,41 nipype.workflow INFO:
	 [Node] Executing "mask_template" <nipype.interfaces.afni.
utils.Calc>
260717-00:51:35,45 nipype.workflow INFO:
	 [Node] Finished "voxel_size_chooser", elapsed time 0.0316
36s.
260717-00:51:35,48 nipype.interface WARNING:
	 Changing /home/jovyan/workspace/books/examples/diffus
ion_imaging/qsirecon-output/sub-CON01/ses-preop/dwi/sub-CON01_ses-preop_acq-AP_space-ACPC_seg-AAL116
_dseg.nii.gz dtype from float64 to int16
260717-00:51:35,952 nipype.workflow INFO:
	 [Node] Finished "mask_template", elapsed time 0.910638s.
260717-00:51:37,45 nipype.workflow INFO:
	 [Node] Setting-up "qsirecon_1_1_wf.sub-CON01_mrtrix_multi
shell_msmt_noACT.sub_CON01_ses_preop_acq_AP_space_ACPC_desc_preproc_dwi_specific_anat_wf.reorient_to
_lps" in "/home/jovyan/workspace/books/examples/diffusion_imaging/qsirecon-work/qsirecon_1_1_wf/sub-
CON01_mrtrix_multishell_msmt_noACT/sub_CON01_ses_preop_acq_AP_space_ACPC_desc_preproc_dwi_specific_a
nat_wf/reorient_to_lps".
260717-00:51:37,48 nipype.workflow INFO:
	 [Node] Executing "reorient_to_lps" <nipype.interfaces.afn
i.utils.Resample>
260717-00:51:37,475 nipype.workflow INFO:
	 [Node] Finished "reorient_to_lps", elapsed time 0.426105
s.
260717-00:51:39,48 nipype.workflow INFO:
	 [Node] Setting-up "qsirecon_1_1_wf.sub-CON01_mrtrix_multi
shell_msmt_noACT.sub_CON01_ses_preop_acq_AP_space_ACPC_desc_preproc_dwi_specific_anat_wf.output_grid
_wf.autobox_template" in "/home/jovyan/workspace/books/examples/diffusion_imaging/qsirecon-work/qsir
econ_1_1_wf/sub-CON01_mrtrix_multishell_msmt_noACT/sub_CON01_ses_preop_acq_AP_space_ACPC_desc_prepro
c_dwi_specific_anat_wf/output_grid_wf/autobox_template".
260717-00:51:39,51 nipype.workflow INFO:
	 [Node] Executing "autobox_template" <nipype.interfaces.af
ni.utils.Autobox>
260717-00:51:39,651 nipype.workflow INFO:
	 [Node] Finished "autobox_template", elapsed time 0.59924
8s.
260717-00:51:41,53 nipype.workflow INFO:
	 [Node] Setting-up "qsirecon_1_1_wf.sub-CON01_mrtrix_multi
shell_msmt_noACT.sub_CON01_ses_preop_acq_AP_space_ACPC_desc_preproc_dwi_specific_anat_wf.output_grid
_wf.deoblique_autobox" in "/home/jovyan/workspace/books/examples/diffusion_imaging/qsirecon-work/qsi
recon_1_1_wf/sub-CON01_mrtrix_multishell_msmt_noACT/sub_CON01_ses_preop_acq_AP_space_ACPC_desc_prepr
oc_dwi_specific_anat_wf/output_grid_wf/deoblique_autobox".
260717-00:51:41,55 nipype.workflow INFO:
	 [Node] Executing "deoblique_autobox" <nipype.interfaces.a
fni.preprocess.Warp>
260717-00:51:41,731 nipype.workflow INFO:
	 [Node] Finished "deoblique_autobox", elapsed time 0.6746
41s.
260717-00:51:43,19 nipype.workflow INFO:
	 [Node] Setting-up "qsirecon_1_1_wf.sub-CON01_mrtrix_multi
shell_msmt_noACT.sub_CON01_ses_preop_acq_AP_space_ACPC_desc_preproc_dwi_specific_anat_wf.output_grid
_wf.resample_to_voxel_size" in "/home/jovyan/workspace/books/examples/diffusion_imaging/qsirecon-wor
k/qsirecon_1_1_wf/sub-CON01_mrtrix_multishell_msmt_noACT/sub_CON01_ses_preop_acq_AP_space_ACPC_desc_
preproc_dwi_specific_anat_wf/output_grid_wf/resample_to_voxel_size".
260717-00:51:43,22 nipype.workflow INFO:
	 [Node] Executing "resample_to_voxel_size" <nipype.interfa
ces.afni.utils.Resample>
260717-00:51:43,160 nipype.workflow INFO:
	 [Node] Finished "resample_to_voxel_size", elapsed time 0
.137558s.
260717-00:51:45,49 nipype.workflow INFO:
	 [Node] Setting-up "qsirecon_1_1_wf.sub-CON01_mrtrix_multi
shell_msmt_noACT.sub_CON01_ses_preop_acq_AP_space_ACPC_desc_preproc_recon_inputs" in "/home/jovyan/w
orkspace/books/examples/diffusion_imaging/qsirecon-work/qsirecon_1_1_wf/sub-CON01_mrtrix_multishell_
msmt_noACT/sub_CON01_ses_preop_acq_AP_space_ACPC_desc_preproc_recon_inputs".
260717-00:51:45,788 nipype.workflow INFO:
	 [Node] Executing "sub_CON01_ses_preop_acq_AP_space_ACPC_
desc_preproc_recon_inputs" <qsirecon.interfaces.interchange.ReconWorkflowInputs>
260717-00:51:45,789 nipype.workflow INFO:
	 [Node] Finished "sub_CON01_ses_preop_acq_AP_space_ACPC_d
esc_preproc_recon_inputs", elapsed time 0.000369s.
260717-00:51:47,26 nipype.workflow INFO:
	 [Node] Setting-up "qsirecon_1_1_wf.sub-CON01_mrtrix_multi
shell_msmt_noACT.sub_CON01_ses_preop_acq_AP_space_ACPC_desc_preproc_recon_wf.msmt_csd.create_mif" in
 "/home/jovyan/workspace/books/examples/diffusion_imaging/qsirecon-work/qsirecon_1_1_wf/sub-CON01_mr
trix_multishell_msmt_noACT/sub_CON01_ses_preop_acq_AP_space_ACPC_desc_preproc_recon_wf/msmt_csd/crea
te_mif".
260717-00:51:47,57 nipype.workflow INFO:
	 [Node] Executing "create_mif" <qsirecon.interfaces.mrtrix
.MRTrixIngress>
260717-00:51:48,628 nipype.interface INFO:
mrconvert: [  0
%] uncompressing image "/home/jovyan/workspace/books/examples/diffusion_imaging/qsiprep-output/sub-C
m
rconvert: [  1%] uncompressing image "/home/jovyan/workspace/books/examples/diffusion_imaging/qsipre
p-output/sub-CON01/ses-preop/dwi/sub-CON01_ses-preop_acq-AP_space-ACPC_desc-preproc_dwi.nii.gz"...
mrconvert: [  2%] uncompressing image "/home/jovyan/workspace/books/examples/diffusion_
imaging/qsiprep-output/sub-CON01/ses-preop/dwi/sub-CON01_ses-preop_acq-AP_space-ACPC_desc-preproc_dw
mrconvert: [  3%] uncompressing image "/home/jovyan/workspace/books/examp
les/diffusion_imaging/qsiprep-output/sub-CON01/ses-preop/dwi/sub-CON01_ses-preop_acq-AP_space-ACPC_d
mrconvert: [  4%] uncompressing image "/home/jovyan/workspa
ce/books/examples/diffusion_imaging/qsiprep-output/sub-CON01/ses-preop/dwi/sub-CON01_ses-preop_acq-A
mrconvert: [  5%] uncompressing image "/home/
jovyan/workspace/books/examples/diffusion_imaging/qsiprep-output/sub-CON01/ses-preop/dwi/sub-CON01_s
mrconvert: [  6%] uncompressing
 image "/home/jovyan/workspace/books/examples/diffusion_imaging/qsiprep-output/sub-CON01/ses-preop/d
mrconvert: [  7%]
 uncompressing image "/home/jovyan/workspace/books/examples/diffusion_imaging/qsiprep-output/sub-CON
mrc
onvert: [  8%] uncompressing image "/home/jovyan/workspace/books/examples/diffusion_imaging/qsiprep-
output/sub-CON01/ses-preop/dwi/sub-CON01_ses-preop_acq-AP_space-ACPC_desc-preproc_dwi.nii.gz"...
mrconvert: [  9%] uncompressing image "/home/jovyan/workspace/books/examples/diffusion_im
aging/qsiprep-output/sub-CON01/ses-preop/dwi/sub-CON01_ses-preop_acq-AP_space-ACPC_desc-preproc_dwi.
mrconvert: [ 10%] uncompressing image "/home/jovyan/workspace/books/example
s/diffusion_imaging/qsiprep-output/sub-CON01/ses-preop/dwi/sub-CON01_ses-preop_acq-AP_space-ACPC_des
mrconvert: [ 11%] uncompressing image "/home/jovyan/workspace
/books/examples/diffusion_imaging/qsiprep-output/sub-CON01/ses-preop/dwi/sub-CON01_ses-preop_acq-AP_
mrconvert: [ 12%] uncompressing image "/home/jo
vyan/workspace/books/examples/diffusion_imaging/qsiprep-output/sub-CON01/ses-preop/dwi/sub-CON01_ses
mrconvert: [ 13%] uncompressing i
mage "/home/jovyan/workspace/books/examples/diffusion_imaging/qsiprep-output/sub-CON01/ses-preop/dwi
mrconvert: [ 14%] u
ncompressing image "/home/jovyan/workspace/books/examples/diffusion_imaging/qsiprep-output/sub-CON01
mrcon
vert: [ 15%] uncompressing image "/home/jovyan/workspace/books/examples/diffusion_imaging/qsiprep-ou
tput/sub-CON01/ses-preop/dwi/sub-CON01_ses-preop_acq-AP_space-ACPC_desc-preproc_dwi.nii.gz"...
mrconvert: [ 16%] uncompressing image "/home/jovyan/workspace/books/examples/diffusion_imag
ing/qsiprep-output/sub-CON01/ses-preop/dwi/sub-CON01_ses-preop_acq-AP_space-ACPC_desc-preproc_dwi.ni
mrconvert: [ 17%] uncompressing image "/home/jovyan/workspace/books/examples/
diffusion_imaging/qsiprep-output/sub-CON01/ses-preop/dwi/sub-CON01_ses-preop_acq-AP_space-ACPC_desc-
mrconvert: [ 18%] uncompressing image "/home/jovyan/workspace/b
ooks/examples/diffusion_imaging/qsiprep-output/sub-CON01/ses-preop/dwi/sub-CON01_ses-preop_acq-AP_sp
mrconvert: [ 19%] uncompressing image "/home/jovy
an/workspace/books/examples/diffusion_imaging/qsiprep-output/sub-CON01/ses-preop/dwi/sub-CON01_ses-p
mrconvert: [ 20%] uncompressing ima
ge "/home/jovyan/workspace/books/examples/diffusion_imaging/qsiprep-output/sub-CON01/ses-preop/dwi/s
mrconvert: [ 21%] unc
ompressing image "/home/jovyan/workspace/books/examples/diffusion_imaging/qsiprep-output/sub-CON01/s
mrconve
rt: [ 22%] uncompressing image "/home/jovyan/workspace/books/examples/diffusion_imaging/qsiprep-outp
ut/sub-CON01/ses-preop/dwi/sub-CON01_ses-preop_acq-AP_space-ACPC_desc-preproc_dwi.nii.gz"...?7
mrconvert: [ 23%] uncompressing image "/home/jovyan/workspace/books/examples/diffusion_imagin
g/qsiprep-output/sub-CON01/ses-preop/dwi/sub-CON01_ses-preop_acq-AP_space-ACPC_desc-preproc_dwi.nii.
mrconvert: [ 24%] uncompressing image "/home/jovyan/workspace/books/examples/di
ffusion_imaging/qsiprep-output/sub-CON01/ses-preop/dwi/sub-CON01_ses-preop_acq-AP_space-ACPC_desc-pr
mrconvert: [ 25%] uncompressing image "/home/jovyan/workspace/boo
ks/examples/diffusion_imaging/qsiprep-output/sub-CON01/ses-preop/dwi/sub-CON01_ses-preop_acq-AP_spac
mrconvert: [ 26%] uncompressing image "/home/jovyan
/workspace/books/examples/diffusion_imaging/qsiprep-output/sub-CON01/ses-preop/dwi/sub-CON01_ses-pre
mrconvert: [ 27%] uncompressing image
 "/home/jovyan/workspace/books/examples/diffusion_imaging/qsiprep-output/sub-CON01/ses-preop/dwi/sub
mrconvert: [ 28%] uncom
pressing image "/home/jovyan/workspace/books/examples/diffusion_imaging/qsiprep-output/sub-CON01/ses
mrconvert
: [ 29%] uncompressing image "/home/jovyan/workspace/books/examples/diffusion_imaging/qsiprep-output
/sub-CON01/ses-preop/dwi/sub-CON01_ses-preop_acq-AP_space-ACPC_desc-preproc_dwi.nii.gz"...?7h
mrconvert: [ 30%] uncompressing image "/home/jovyan/workspace/books/examples/diffusion_imaging/
qsiprep-output/sub-CON01/ses-preop/dwi/sub-CON01_ses-preop_acq-AP_space-ACPC_desc-preproc_dwi.nii.gz
mrconvert: [ 31%] uncompressing image "/home/jovyan/workspace/books/examples/diff
usion_imaging/qsiprep-output/sub-CON01/ses-preop/dwi/sub-CON01_ses-preop_acq-AP_space-ACPC_desc-prep
mrconvert: [ 32%] uncompressing image "/home/jovyan/workspace/books
/examples/diffusion_imaging/qsiprep-output/sub-CON01/ses-preop/dwi/sub-CON01_ses-preop_acq-AP_space-
mrconvert: [ 33%] uncompressing image "/home/jovyan/w
orkspace/books/examples/diffusion_imaging/qsiprep-output/sub-CON01/ses-preop/dwi/sub-CON01_ses-preop
mrconvert: [ 34%] uncompressing image "
/home/jovyan/workspace/books/examples/diffusion_imaging/qsiprep-output/sub-CON01/ses-preop/dwi/sub-C
mrconvert: [ 35%] uncompr
essing image "/home/jovyan/workspace/books/examples/diffusion_imaging/qsiprep-output/sub-CON01/ses-p
mrconvert:
[ 36%] uncompressing image "/home/jovyan/workspace/books/examples/diffusion_imaging/qsiprep-output/s
ub-CON01/ses-preop/dwi/sub-CON01_ses-preop_acq-AP_space-ACPC_desc-preproc_dwi.nii.gz"...?7h?
mrconvert: [ 37%] uncompressing image "/home/jovyan/workspace/books/examples/diffusion_imaging/qs
iprep-output/sub-CON01/ses-preop/dwi/sub-CON01_ses-preop_acq-AP_space-ACPC_desc-preproc_dwi.nii.gz".
mrconvert: [ 38%] uncompressing image "/home/jovyan/workspace/books/examples/diffus
ion_imaging/qsiprep-output/sub-CON01/ses-preop/dwi/sub-CON01_ses-preop_acq-AP_space-ACPC_desc-prepro
mrconvert: [ 39%] uncompressing image "/home/jovyan/workspace/books/e
xamples/diffusion_imaging/qsiprep-output/sub-CON01/ses-preop/dwi/sub-CON01_ses-preop_acq-AP_space-AC
mrconvert: [ 40%] uncompressing image "/home/jovyan/wor
kspace/books/examples/diffusion_imaging/qsiprep-output/sub-CON01/ses-preop/dwi/sub-CON01_ses-preop_a
mrconvert: [ 41%] uncompressing image "/h
ome/jovyan/workspace/books/examples/diffusion_imaging/qsiprep-output/sub-CON01/ses-preop/dwi/sub-CON
mrconvert: [ 42%] uncompres
sing image "/home/jovyan/workspace/books/examples/diffusion_imaging/qsiprep-output/sub-CON01/ses-pre
mrconvert: [
43%] uncompressing image "/home/jovyan/workspace/books/examples/diffusion_imaging/qsiprep-output/sub
-CON01/ses-preop/dwi/sub-CON01_ses-preop_acq-AP_space-ACPC_desc-preproc_dwi.nii.gz"...?7h?7l
mrconvert: [ 44%] uncompressing image "/home/jovyan/workspace/books/examples/diffusion_imaging/qsip
rep-output/sub-CON01/ses-preop/dwi/sub-CON01_ses-preop_acq-AP_space-ACPC_desc-preproc_dwi.nii.gz"...
mrconvert: [ 45%] uncompressing image "/home/jovyan/workspace/books/examples/diffusio
n_imaging/qsiprep-output/sub-CON01/ses-preop/dwi/sub-CON01_ses-preop_acq-AP_space-ACPC_desc-preproc_
mrconvert: [ 46%] uncompressing image "/home/jovyan/workspace/books/exa
mples/diffusion_imaging/qsiprep-output/sub-CON01/ses-preop/dwi/sub-CON01_ses-preop_acq-AP_space-ACPC
mrconvert: [ 47%] uncompressing image "/home/jovyan/works
pace/books/examples/diffusion_imaging/qsiprep-output/sub-CON01/ses-preop/dwi/sub-CON01_ses-preop_acq
mrconvert: [ 48%] uncompressing image "/hom
e/jovyan/workspace/books/examples/diffusion_imaging/qsiprep-output/sub-CON01/ses-preop/dwi/sub-CON01
mrconvert: [ 49%] uncompressi
ng image "/home/jovyan/workspace/books/examples/diffusion_imaging/qsiprep-output/sub-CON01/ses-preop
mrconvert: [ 50
%] uncompressing image "/home/jovyan/workspace/books/examples/diffusion_imaging/qsiprep-output/sub-C
m
rconvert: [ 51%] uncompressing image "/home/jovyan/workspace/books/examples/diffusion_imaging/qsipre
p-output/sub-CON01/ses-preop/dwi/sub-CON01_ses-preop_acq-AP_space-ACPC_desc-preproc_dwi.nii.gz"...
mrconvert: [ 52%] uncompressing image "/home/jovyan/workspace/books/examples/diffusion_
imaging/qsiprep-output/sub-CON01/ses-preop/dwi/sub-CON01_ses-preop_acq-AP_space-ACPC_desc-preproc_dw
mrconvert: [ 53%] uncompressing image "/home/jovyan/workspace/books/examp
les/diffusion_imaging/qsiprep-output/sub-CON01/ses-preop/dwi/sub-CON01_ses-preop_acq-AP_space-ACPC_d
mrconvert: [ 54%] uncompressing image "/home/jovyan/workspa
ce/books/examples/diffusion_imaging/qsiprep-output/sub-CON01/ses-preop/dwi/sub-CON01_ses-preop_acq-A
mrconvert: [ 55%] uncompressing image "/home/
jovyan/workspace/books/examples/diffusion_imaging/qsiprep-output/sub-CON01/ses-preop/dwi/sub-CON01_s
mrconvert: [ 56%] uncompressing
 image "/home/jovyan/workspace/books/examples/diffusion_imaging/qsiprep-output/sub-CON01/ses-preop/d
mrconvert: [ 57%]
 uncompressing image "/home/jovyan/workspace/books/examples/diffusion_imaging/qsiprep-output/sub-CON
mrc
onvert: [ 58%] uncompressing image "/home/jovyan/workspace/books/examples/diffusion_imaging/qsiprep-
output/sub-CON01/ses-preop/dwi/sub-CON01_ses-preop_acq-AP_space-ACPC_desc-preproc_dwi.nii.gz"...
mrconvert: [ 59%] uncompressing image "/home/jovyan/workspace/books/examples/diffusion_im
aging/qsiprep-output/sub-CON01/ses-preop/dwi/sub-CON01_ses-preop_acq-AP_space-ACPC_desc-preproc_dwi.
mrconvert: [ 60%] uncompressing image "/home/jovyan/workspace/books/example
s/diffusion_imaging/qsiprep-output/sub-CON01/ses-preop/dwi/sub-CON01_ses-preop_acq-AP_space-ACPC_des
mrconvert: [ 61%] uncompressing image "/home/jovyan/workspace
/books/examples/diffusion_imaging/qsiprep-output/sub-CON01/ses-preop/dwi/sub-CON01_ses-preop_acq-AP_
mrconvert: [ 62%] uncompressing image "/home/jo
vyan/workspace/books/examples/diffusion_imaging/qsiprep-output/sub-CON01/ses-preop/dwi/sub-CON01_ses
mrconvert: [ 63%] uncompressing i
mage "/home/jovyan/workspace/books/examples/diffusion_imaging/qsiprep-output/sub-CON01/ses-preop/dwi
mrconvert: [ 64%] u
ncompressing image "/home/jovyan/workspace/books/examples/diffusion_imaging/qsiprep-output/sub-CON01
mrcon
vert: [ 65%] uncompressing image "/home/jovyan/workspace/books/examples/diffusion_imaging/qsiprep-ou
tput/sub-CON01/ses-preop/dwi/sub-CON01_ses-preop_acq-AP_space-ACPC_desc-preproc_dwi.nii.gz"...
mrconvert: [ 66%] uncompressing image "/home/jovyan/workspace/books/examples/diffusion_imag
ing/qsiprep-output/sub-CON01/ses-preop/dwi/sub-CON01_ses-preop_acq-AP_space-ACPC_desc-preproc_dwi.ni
mrconvert: [ 67%] uncompressing image "/home/jovyan/workspace/books/examples/
diffusion_imaging/qsiprep-output/sub-CON01/ses-preop/dwi/sub-CON01_ses-preop_acq-AP_space-ACPC_desc-
mrconvert: [ 68%] uncompressing image "/home/jovyan/workspace/b
ooks/examples/diffusion_imaging/qsiprep-output/sub-CON01/ses-preop/dwi/sub-CON01_ses-preop_acq-AP_sp
mrconvert: [ 69%] uncompressing image "/home/jovy
an/workspace/books/examples/diffusion_imaging/qsiprep-output/sub-CON01/ses-preop/dwi/sub-CON01_ses-p
mrconvert: [ 70%] uncompressing ima
ge "/home/jovyan/workspace/books/examples/diffusion_imaging/qsiprep-output/sub-CON01/ses-preop/dwi/s
mrconvert: [ 71%] unc
ompressing image "/home/jovyan/workspace/books/examples/diffusion_imaging/qsiprep-output/sub-CON01/s
mrconve
rt: [ 72%] uncompressing image "/home/jovyan/workspace/books/examples/diffusion_imaging/qsiprep-outp
ut/sub-CON01/ses-preop/dwi/sub-CON01_ses-preop_acq-AP_space-ACPC_desc-preproc_dwi.nii.gz"...?7
mrconvert: [ 73%] uncompressing image "/home/jovyan/workspace/books/examples/diffusion_imagin
g/qsiprep-output/sub-CON01/ses-preop/dwi/sub-CON01_ses-preop_acq-AP_space-ACPC_desc-preproc_dwi.nii.
mrconvert: [ 74%] uncompressing image "/home/jovyan/workspace/books/examples/di
ffusion_imaging/qsiprep-output/sub-CON01/ses-preop/dwi/sub-CON01_ses-preop_acq-AP_space-ACPC_desc-pr
mrconvert: [ 75%] uncompressing image "/home/jovyan/workspace/boo
ks/examples/diffusion_imaging/qsiprep-output/sub-CON01/ses-preop/dwi/sub-CON01_ses-preop_acq-AP_spac
mrconvert: [ 76%] uncompressing image "/home/jovyan
/workspace/books/examples/diffusion_imaging/qsiprep-output/sub-CON01/ses-preop/dwi/sub-CON01_ses-pre
mrconvert: [ 77%] uncompressing image
 "/home/jovyan/workspace/books/examples/diffusion_imaging/qsiprep-output/sub-CON01/ses-preop/dwi/sub
mrconvert: [ 78%] uncom
pressing image "/home/jovyan/workspace/books/examples/diffusion_imaging/qsiprep-output/sub-CON01/ses
mrconvert
: [ 79%] uncompressing image "/home/jovyan/workspace/books/examples/diffusion_imaging/qsiprep-output
/sub-CON01/ses-preop/dwi/sub-CON01_ses-preop_acq-AP_space-ACPC_desc-preproc_dwi.nii.gz"...?7h
mrconvert: [ 80%] uncompressing image "/home/jovyan/workspace/books/examples/diffusion_imaging/
qsiprep-output/sub-CON01/ses-preop/dwi/sub-CON01_ses-preop_acq-AP_space-ACPC_desc-preproc_dwi.nii.gz
mrconvert: [ 81%] uncompressing image "/home/jovyan/workspace/books/examples/diff
usion_imaging/qsiprep-output/sub-CON01/ses-preop/dwi/sub-CON01_ses-preop_acq-AP_space-ACPC_desc-prep
mrconvert: [ 82%] uncompressing image "/home/jovyan/workspace/books
/examples/diffusion_imaging/qsiprep-output/sub-CON01/ses-preop/dwi/sub-CON01_ses-preop_acq-AP_space-
mrconvert: [ 83%] uncompressing image "/home/jovyan/w
orkspace/books/examples/diffusion_imaging/qsiprep-output/sub-CON01/ses-preop/dwi/sub-CON01_ses-preop
mrconvert: [ 84%] uncompressing image "
/home/jovyan/workspace/books/examples/diffusion_imaging/qsiprep-output/sub-CON01/ses-preop/dwi/sub-C
mrconvert: [ 85%] uncompr
essing image "/home/jovyan/workspace/books/examples/diffusion_imaging/qsiprep-output/sub-CON01/ses-p
mrconvert:
[ 86%] uncompressing image "/home/jovyan/workspace/books/examples/diffusion_imaging/qsiprep-output/s
ub-CON01/ses-preop/dwi/sub-CON01_ses-preop_acq-AP_space-ACPC_desc-preproc_dwi.nii.gz"...?7h?
mrconvert: [ 87%] uncompressing image "/home/jovyan/workspace/books/examples/diffusion_imaging/qs
iprep-output/sub-CON01/ses-preop/dwi/sub-CON01_ses-preop_acq-AP_space-ACPC_desc-preproc_dwi.nii.gz".
mrconvert: [ 88%] uncompressing image "/home/jovyan/workspace/books/examples/diffus
ion_imaging/qsiprep-output/sub-CON01/ses-preop/dwi/sub-CON01_ses-preop_acq-AP_space-ACPC_desc-prepro
mrconvert: [ 89%] uncompressing image "/home/jovyan/workspace/books/e
xamples/diffusion_imaging/qsiprep-output/sub-CON01/ses-preop/dwi/sub-CON01_ses-preop_acq-AP_space-AC
mrconvert: [ 90%] uncompressing image "/home/jovyan/wor
kspace/books/examples/diffusion_imaging/qsiprep-output/sub-CON01/ses-preop/dwi/sub-CON01_ses-preop_a
mrconvert: [ 91%] uncompressing image "/h
ome/jovyan/workspace/books/examples/diffusion_imaging/qsiprep-output/sub-CON01/ses-preop/dwi/sub-CON
mrconvert: [ 92%] uncompres
sing image "/home/jovyan/workspace/books/examples/diffusion_imaging/qsiprep-output/sub-CON01/ses-pre
mrconvert: [
93%] uncompressing image "/home/jovyan/workspace/books/examples/diffusion_imaging/qsiprep-output/sub
-CON01/ses-preop/dwi/sub-CON01_ses-preop_acq-AP_space-ACPC_desc-preproc_dwi.nii.gz"...?7h?7l
mrconvert: [ 94%] uncompressing image "/home/jovyan/workspace/books/examples/diffusion_imaging/qsip
rep-output/sub-CON01/ses-preop/dwi/sub-CON01_ses-preop_acq-AP_space-ACPC_desc-preproc_dwi.nii.gz"...
mrconvert: [ 95%] uncompressing image "/home/jovyan/workspace/books/examples/diffusio
n_imaging/qsiprep-output/sub-CON01/ses-preop/dwi/sub-CON01_ses-preop_acq-AP_space-ACPC_desc-preproc_
mrconvert: [ 96%] uncompressing image "/home/jovyan/workspace/books/exa
mples/diffusion_imaging/qsiprep-output/sub-CON01/ses-preop/dwi/sub-CON01_ses-preop_acq-AP_space-ACPC
mrconvert: [ 97%] uncompressing image "/home/jovyan/works
pace/books/examples/diffusion_imaging/qsiprep-output/sub-CON01/ses-preop/dwi/sub-CON01_ses-preop_acq
mrconvert: [ 98%] uncompressing image "/hom
e/jovyan/workspace/books/examples/diffusion_imaging/qsiprep-output/sub-CON01/ses-preop/dwi/sub-CON01
mrconvert: [ 99%] uncompressi
ng image "/home/jovyan/workspace/books/examples/diffusion_imaging/qsiprep-output/sub-CON01/ses-preop
mrconvert: [100
%] uncompressing image "/home/jovyan/workspace/books/examples/diffusion_imaging/qsiprep-output/sub-C
mrconv
ert: [100%] uncompressing image "/home/jovyan/workspace/books/examples/diffusion_imaging/qsiprep-out
put/sub-CON01/ses-preop/dwi/sub-CON01_ses-preop_acq-AP_space-ACPC_desc-preproc_dwi.nii.gz"
260717-00:51:49,868 nipype.interface INFO:
mrconvert: [  0
%] copying from "/home/jovy...CPC_desc-preproc_dwi.nii.gz" to "/home/jovy...e-ACPC_desc-preproc_dwi.
mrconvert: [  1%] copying from "/home/jovy...CPC_desc-preproc_dwi.nii.gz" to "
mrconvert: [  2%] copying from "/home/jov
mrco
nvert: [  3%] copying from "/home/jovy...CPC_desc-preproc_dwi.nii.gz" to "/home/jovy...e-ACPC_desc-p
mrconvert: [  4%] copying from "/home/jovy...CPC_desc-preproc_dwi.n
mrconvert: [  5%] copying from
 "/home/jovy...CPC_desc-preproc_dwi.nii.gz" to "/home/jovy...e-ACPC_desc-preproc_dwi.mif"...?7
mrconvert: [  6%] copying from "/home/jovy...CPC_desc-preproc_dwi.nii.gz" to "/home/jovy...e-
mrconvert: [  7%] copying from "/home/jovy...CPC_desc-pr
mrconvert: [  8%] c
opying from "/home/jovy...CPC_desc-preproc_dwi.nii.gz" to "/home/jovy...e-ACPC_desc-preproc_dwi.mif"
mrconvert: [  9%] copying from "/home/jovy...CPC_desc-preproc_dwi.nii.gz" to "/hom
mrconvert: [ 10%] copying from "/home/jovy...
mrconver
t: [ 11%] copying from "/home/jovy...CPC_desc-preproc_dwi.nii.gz" to "/home/jovy...e-ACPC_desc-prepr
mrconvert: [ 12%] copying from "/home/jovy...CPC_desc-preproc_dwi.nii.g
mrconvert: [ 13%] copying from "/h
ome/jovy...CPC_desc-preproc_dwi.nii.gz" to "/home/jovy...e-ACPC_desc-preproc_dwi.mif"...?7h?
mrconvert: [ 14%] copying from "/home/jovy...CPC_desc-preproc_dwi.nii.gz" to "/home/jovy...e-ACPC
mrconvert: [ 15%] copying from "/home/jovy...CPC_desc-prepro
mrconvert: [ 16%] copyi
ng from "/home/jovy...CPC_desc-preproc_dwi.nii.gz" to "/home/jovy...e-ACPC_desc-preproc_dwi.mif"...
mrconvert: [ 17%] copying from "/home/jovy...CPC_desc-preproc_dwi.nii.gz" to "/home/jo
mrconvert: [ 18%] copying from "/home/jovy...CPC_
mrconvert: [
 19%] copying from "/home/jovy...CPC_desc-preproc_dwi.nii.gz" to "/home/jovy...e-ACPC_desc-preproc_d
mrconvert: [ 20%] copying from "/home/jovy...CPC_desc-preproc_dwi.nii.gz" t
mrconvert: [ 21%] copying from "/home/
m
rconvert: [ 22%] copying from "/home/jovy...CPC_desc-preproc_dwi.nii.gz" to "/home/jovy...e-ACPC_des
mrconvert: [ 23%] copying from "/home/jovy...CPC_desc-preproc_dw
mrconvert: [ 24%] copying f
rom "/home/jovy...CPC_desc-preproc_dwi.nii.gz" to "/home/jovy...e-ACPC_desc-preproc_dwi.mif"...
mrconvert: [ 25%] copying from "/home/jovy...CPC_desc-preproc_dwi.nii.gz" to "/home/jovy..
mrconvert: [ 26%] copying from "/home/jovy...CPC_desc
mrconvert: [ 27%
] copying from "/home/jovy...CPC_desc-preproc_dwi.nii.gz" to "/home/jovy...e-ACPC_desc-preproc_dwi.m
mrconvert: [ 28%] copying from "/home/jovy...CPC_desc-preproc_dwi.nii.gz" to "/
mrconvert: [ 29%] copying from "/home/jovy
mrcon
vert: [ 30%] copying from "/home/jovy...CPC_desc-preproc_dwi.nii.gz" to "/home/jovy...e-ACPC_desc-pr
mrconvert: [ 31%] copying from "/home/jovy...CPC_desc-preproc_dwi.ni
mrconvert: [ 32%] copying from
"/home/jovy...CPC_desc-preproc_dwi.nii.gz" to "/home/jovy...e-ACPC_desc-preproc_dwi.mif"...?7h
mrconvert: [ 33%] copying from "/home/jovy...CPC_desc-preproc_dwi.nii.gz" to "/home/jovy...e-A
mrconvert: [ 34%] copying from "/home/jovy...CPC_desc-pre
mrconvert: [ 35%] co
pying from "/home/jovy...CPC_desc-preproc_dwi.nii.gz" to "/home/jovy...e-ACPC_desc-preproc_dwi.mif".
mrconvert: [ 36%] copying from "/home/jovy...CPC_desc-preproc_dwi.nii.gz" to "/home
mrconvert: [ 37%] copying from "/home/jovy...C
mrconvert
: [ 38%] copying from "/home/jovy...CPC_desc-preproc_dwi.nii.gz" to "/home/jovy...e-ACPC_desc-prepro
mrconvert: [ 39%] copying from "/home/jovy...CPC_desc-preproc_dwi.nii.gz
mrconvert: [ 40%] copying from "/ho
me/jovy...CPC_desc-preproc_dwi.nii.gz" to "/home/jovy...e-ACPC_desc-preproc_dwi.mif"...?7h?7
mrconvert: [ 41%] copying from "/home/jovy...CPC_desc-preproc_dwi.nii.gz" to "/home/jovy...e-ACPC_
mrconvert: [ 42%] copying from "/home/jovy...CPC_desc-preproc
mrconvert: [ 43%] copyin
g from "/home/jovy...CPC_desc-preproc_dwi.nii.gz" to "/home/jovy...e-ACPC_desc-preproc_dwi.mif"...
mrconvert: [ 44%] copying from "/home/jovy...CPC_desc-preproc_dwi.nii.gz" to "/home/jov
mrconvert: [ 45%] copying from "/home/jovy...CPC_d
mrconvert: [
46%] copying from "/home/jovy...CPC_desc-preproc_dwi.nii.gz" to "/home/jovy...e-ACPC_desc-preproc_dw
mrconvert: [ 47%] copying from "/home/jovy...CPC_desc-preproc_dwi.nii.gz" to
mrconvert: [ 48%] copying from "/home/j
mr
convert: [ 49%] copying from "/home/jovy...CPC_desc-preproc_dwi.nii.gz" to "/home/jovy...e-ACPC_desc
mrconvert: [ 50%] copying from "/home/jovy...CPC_desc-preproc_dwi
mrconvert: [ 51%] copying fr
om "/home/jovy...CPC_desc-preproc_dwi.nii.gz" to "/home/jovy...e-ACPC_desc-preproc_dwi.mif"...
mrconvert: [ 52%] copying from "/home/jovy...CPC_desc-preproc_dwi.nii.gz" to "/home/jovy...
mrconvert: [ 53%] copying from "/home/jovy...CPC_desc-
mrconvert: [ 54%]
 copying from "/home/jovy...CPC_desc-preproc_dwi.nii.gz" to "/home/jovy...e-ACPC_desc-preproc_dwi.mi
mrconvert: [ 55%] copying from "/home/jovy...CPC_desc-preproc_dwi.nii.gz" to "/h
mrconvert: [ 56%] copying from "/home/jovy.
mrconv
ert: [ 57%] copying from "/home/jovy...CPC_desc-preproc_dwi.nii.gz" to "/home/jovy...e-ACPC_desc-pre
mrconvert: [ 58%] copying from "/home/jovy...CPC_desc-preproc_dwi.nii
mrconvert: [ 59%] copying from "
/home/jovy...CPC_desc-preproc_dwi.nii.gz" to "/home/jovy...e-ACPC_desc-preproc_dwi.mif"...?7h
mrconvert: [ 60%] copying from "/home/jovy...CPC_desc-preproc_dwi.nii.gz" to "/home/jovy...e-AC
mrconvert: [ 61%] copying from "/home/jovy...CPC_desc-prep
mrconvert: [ 62%] cop
ying from "/home/jovy...CPC_desc-preproc_dwi.nii.gz" to "/home/jovy...e-ACPC_desc-preproc_dwi.mif"..
mrconvert: [ 63%] copying from "/home/jovy...CPC_desc-preproc_dwi.nii.gz" to "/home/
mrconvert: [ 64%] copying from "/home/jovy...CP
mrconvert:
 [ 65%] copying from "/home/jovy...CPC_desc-preproc_dwi.nii.gz" to "/home/jovy...e-ACPC_desc-preproc
mrconvert: [ 66%] copying from "/home/jovy...CPC_desc-preproc_dwi.nii.gz"
mrconvert: [ 67%] copying from "/hom
e/jovy...CPC_desc-preproc_dwi.nii.gz" to "/home/jovy...e-ACPC_desc-preproc_dwi.mif"...?7h?7l
mrconvert: [ 68%] copying from "/home/jovy...CPC_desc-preproc_dwi.nii.gz" to "/home/jovy...e-ACPC_d
mrconvert: [ 69%] copying from "/home/jovy...CPC_desc-preproc_
mrconvert: [ 70%] copying
 from "/home/jovy...CPC_desc-preproc_dwi.nii.gz" to "/home/jovy...e-ACPC_desc-preproc_dwi.mif"...0
mrconvert: [ 71%] copying from "/home/jovy...CPC_desc-preproc_dwi.nii.gz" to "/home/jovy
mrconvert: [ 72%] copying from "/home/jovy...CPC_de
mrconvert: [ 7
3%] copying from "/home/jovy...CPC_desc-preproc_dwi.nii.gz" to "/home/jovy...e-ACPC_desc-preproc_dwi
mrconvert: [ 74%] copying from "/home/jovy...CPC_desc-preproc_dwi.nii.gz" to
mrconvert: [ 75%] copying from "/home/jo
mrc
onvert: [ 76%] copying from "/home/jovy...CPC_desc-preproc_dwi.nii.gz" to "/home/jovy...e-ACPC_desc-
mrconvert: [ 77%] copying from "/home/jovy...CPC_desc-preproc_dwi.
mrconvert: [ 78%] copying fro
m "/home/jovy...CPC_desc-preproc_dwi.nii.gz" to "/home/jovy...e-ACPC_desc-preproc_dwi.mif"...?
mrconvert: [ 79%] copying from "/home/jovy...CPC_desc-preproc_dwi.nii.gz" to "/home/jovy...e
mrconvert: [ 80%] copying from "/home/jovy...CPC_desc-p
mrconvert: [ 81%]
copying from "/home/jovy...CPC_desc-preproc_dwi.nii.gz" to "/home/jovy...e-ACPC_desc-preproc_dwi.mif
mrconvert: [ 82%] copying from "/home/jovy...CPC_desc-preproc_dwi.nii.gz" to "/ho
mrconvert: [ 83%] copying from "/home/jovy..
mrconve
rt: [ 84%] copying from "/home/jovy...CPC_desc-preproc_dwi.nii.gz" to "/home/jovy...e-ACPC_desc-prep
mrconvert: [ 85%] copying from "/home/jovy...CPC_desc-preproc_dwi.nii.
mrconvert: [ 86%] copying from "/
home/jovy...CPC_desc-preproc_dwi.nii.gz" to "/home/jovy...e-ACPC_desc-preproc_dwi.mif"...?7h
mrconvert: [ 87%] copying from "/home/jovy...CPC_desc-preproc_dwi.nii.gz" to "/home/jovy...e-ACP
mrconvert: [ 88%] copying from "/home/jovy...CPC_desc-prepr
mrconvert: [ 89%] copy
ing from "/home/jovy...CPC_desc-preproc_dwi.nii.gz" to "/home/jovy...e-ACPC_desc-preproc_dwi.mif"...
mrconvert: [ 90%] copying from "/home/jovy...CPC_desc-preproc_dwi.nii.gz" to "/home/j
mrconvert: [ 91%] copying from "/home/jovy...CPC
mrconvert:
[ 92%] copying from "/home/jovy...CPC_desc-preproc_dwi.nii.gz" to "/home/jovy...e-ACPC_desc-preproc_
mrconvert: [ 93%] copying from "/home/jovy...CPC_desc-preproc_dwi.nii.gz"
mrconvert: [ 94%] copying from "/home
/jovy...CPC_desc-preproc_dwi.nii.gz" to "/home/jovy...e-ACPC_desc-preproc_dwi.mif"...?7h?7l
mrconvert: [ 95%] copying from "/home/jovy...CPC_desc-preproc_dwi.nii.gz" to "/home/jovy...e-ACPC_de
mrconvert: [ 96%] copying from "/home/jovy...CPC_desc-preproc_d
mrconvert: [ 97%] copying
from "/home/jovy...CPC_desc-preproc_dwi.nii.gz" to "/home/jovy...e-ACPC_desc-preproc_dwi.mif"...
mrconvert: [ 98%] copying from "/home/jovy...CPC_desc-preproc_dwi.nii.gz" to "/home/jovy.
mrconvert: [ 99%] copying from "/home/jovy...CPC_des
mrconvert: [100
%] copying from "/home/jovy...CPC_desc-preproc_dwi.nii.gz" to "/home/jovy...e-ACPC_desc-preproc_dwi.
mrconvert: [100%] copying from "/home/jovy...CPC_desc-preproc_dwi.nii.gz" to "/home
/jovy...e-ACPC_desc-preproc_dwi.mif"
260717-00:51:49,945 nipype.workflow INFO:
	 [Node] Finished "create_mif", elapsed time 2.887287s.
260717-00:51:51,32 nipype.workflow INFO:
	 [Node] Setting-up "qsirecon_1_1_wf.sub-CON01_mrtrix_multi
shell_msmt_noACT.sub_CON01_ses_preop_acq_AP_space_ACPC_desc_preproc_recon_wf.msmt_csd.estimate_respo
nse" in "/home/jovyan/workspace/books/examples/diffusion_imaging/qsirecon-work/qsirecon_1_1_wf/sub-C
ON01_mrtrix_multishell_msmt_noACT/sub_CON01_ses_preop_acq_AP_space_ACPC_desc_preproc_recon_wf/msmt_c
sd/estimate_response".
260717-00:51:51,60 nipype.workflow INFO:
	 [Node] Executing "estimate_response" <qsirecon.interfaces
.mrtrix.SS3TDwi2Response>
260717-00:52:00,513 nipype.workflow INFO:
	 [Node] Finished "estimate_response", elapsed time 9.3774
31s.
260717-00:52:01,45 nipype.workflow INFO:
	 [Node] Setting-up "qsirecon_1_1_wf.sub-CON01_mrtrix_multi
shell_msmt_noACT.sub_CON01_ses_preop_acq_AP_space_ACPC_desc_preproc_recon_wf.msmt_csd.estimate_fod"
in "/home/jovyan/workspace/books/examples/diffusion_imaging/qsirecon-work/qsirecon_1_1_wf/sub-CON01_
mrtrix_multishell_msmt_noACT/sub_CON01_ses_preop_acq_AP_space_ACPC_desc_preproc_recon_wf/msmt_csd/es
timate_fod".
260717-00:52:01,74 nipype.workflow INFO:
	 [Node] Executing "estimate_fod" <qsirecon.interfaces.mrtr
ix.EstimateFOD>
260717-01:09:54,735 nipype.workflow INFO:
	 [Node] Finished "estimate_fod", elapsed time 1073.577656
s.
260717-01:09:56,138 nipype.workflow INFO:
	 [Node] Setting-up "qsirecon_1_1_wf.sub-CON01_mrtrix_mult
ishell_msmt_noACT.sub_CON01_ses_preop_acq_AP_space_ACPC_desc_preproc_recon_wf.msmt_csd.intensity_nor
m" in "/home/jovyan/workspace/books/examples/diffusion_imaging/qsirecon-work/qsirecon_1_1_wf/sub-CON
01_mrtrix_multishell_msmt_noACT/sub_CON01_ses_preop_acq_AP_space_ACPC_desc_preproc_recon_wf/msmt_csd
/intensity_norm".
260717-01:09:56,145 nipype.workflow INFO:
	 [Node] Executing "intensity_norm" <qsirecon.interfaces.m
rtrix.MTNormalize>
260717-01:09:59,558 nipype.workflow INFO:
	 [Node] Finished "intensity_norm", elapsed time 3.210207s
.
260717-01:10:01,0 nipype.workflow INFO:
	 [Node] Setting-up "qsirecon_1_1_wf.sub-CON01_mrtrix_multis
hell_msmt_noACT.sub_CON01_ses_preop_acq_AP_space_ACPC_desc_preproc_recon_wf.msmt_csd.plot_peaks" in
"/home/jovyan/workspace/books/examples/diffusion_imaging/qsirecon-work/qsirecon_1_1_wf/sub-CON01_mrt
rix_multishell_msmt_noACT/sub_CON01_ses_preop_acq_AP_space_ACPC_desc_preproc_recon_wf/msmt_csd/plot_
peaks".
260717-01:10:01,3 nipype.workflow INFO:
	 [Node] Executing "plot_peaks" <qsirecon.interfaces.reports
.CLIReconPeaksReport>
260717-01:10:05,329 nipype.workflow INFO:
	 [Node] Setting-up "qsirecon_1_1_wf.sub-CON01_mrtrix_mult
ishell_msmt_noACT.sub_CON01_ses_preop_acq_AP_space_ACPC_desc_preproc_recon_wf.track_ifod2.tractograp
hy" in "/home/jovyan/workspace/books/examples/diffusion_imaging/qsirecon-work/qsirecon_1_1_wf/sub-CO
N01_mrtrix_multishell_msmt_noACT/sub_CON01_ses_preop_acq_AP_space_ACPC_desc_preproc_recon_wf/track_i
fod2/tractography".
260717-01:10:05,333 nipype.workflow INFO:
	 [Node] Executing "tractography" <qsirecon.interfaces.mrt
rix.TckGen>
260717-01:10:41,958 nipype.workflow INFO:
	 [Node] Finished "plot_peaks", elapsed time 40.953721s.
260717-01:15:40,295 nipype.workflow INFO:
	 [Node] Finished "tractography", elapsed time 334.961534s
.
260717-01:15:41,686 nipype.workflow INFO:
	 [Node] Setting-up "qsirecon_1_1_wf.sub-CON01_mrtrix_mult
ishell_msmt_noACT.sub_CON01_ses_preop_acq_AP_space_ACPC_desc_preproc_recon_wf.track_ifod2.tck_sift2"
 in "/home/jovyan/workspace/books/examples/diffusion_imaging/qsirecon-work/qsirecon_1_1_wf/sub-CON01
_mrtrix_multishell_msmt_noACT/sub_CON01_ses_preop_acq_AP_space_ACPC_desc_preproc_recon_wf/track_ifod
2/tck_sift2".
260717-01:15:41,690 nipype.workflow INFO:
	 [Node] Executing "tck_sift2" <qsirecon.interfaces.mrtrix
.SIFT2>
260717-01:16:26,617 nipype.workflow INFO:
	 [Node] Finished "tck_sift2", elapsed time 44.92635s.
260717-01:16:27,842 nipype.workflow INFO:
	 [Node] Setting-up "qsirecon_1_1_wf.sub-CON01_mrtrix_mult
ishell_msmt_noACT.sub_CON01_ses_preop_acq_AP_space_ACPC_desc_preproc_recon_wf.mrtrix_conn.calc_conne
ctivity" in "/home/jovyan/workspace/books/examples/diffusion_imaging/qsirecon-work/qsirecon_1_1_wf/s
ub-CON01_mrtrix_multishell_msmt_noACT/sub_CON01_ses_preop_acq_AP_space_ACPC_desc_preproc_recon_wf/mr
trix_conn/calc_connectivity".
260717-01:16:27,849 nipype.workflow INFO:
	 [Node] Executing "calc_connectivity" <qsirecon.interface
s.mrtrix.MRTrixAtlasGraph>
260717-01:16:27,862 nipype.workflow INFO:
	 Workflow mrtrix_atlasgraph settings: ['check', 'executio
n', 'logging', 'monitoring']
260717-01:16:27,870 nipype.workflow INFO:
	 Running in parallel.
260717-01:16:27,873 nipype.workflow INFO:
	 [MultiProc] Running 0 tasks, and 4 jobs ready. Free memo
ry (GB): 56.51/56.51, Free processors: 4/4.
260717-01:16:29,875 nipype.workflow INFO:
	 [MultiProc] Running 1 tasks, and 3 jobs ready. Free memo
ry (GB): 56.31/56.51, Free processors: 0/4.
                     Currently running:
       * mrtrix_atlasgraph.AAL116_sift_invnodevol_radius2_count
260717-01:16:33,191 nipype.workflow INFO:
	 [Node] Setting-up "mrtrix_atlasgraph.AAL116_sift_invnode
vol_radius2_count" in "/home/jovyan/workspace/books/examples/diffusion_imaging/qsirecon-work/qsireco
n_1_1_wf/sub-CON01_mrtrix_multishell_msmt_noACT/sub_CON01_ses_preop_acq_AP_space_ACPC_desc_preproc_r
econ_wf/mrtrix_conn/calc_connectivity/mrtrix_atlasgraph/AAL116_sift_invnodevol_radius2_count".
260717-01:16:33,193 nipype.workflow INFO:
	 [Node] Executing "AAL116_sift_invnodevol_radius2_count"
<qsirecon.interfaces.mrtrix.BuildConnectome>
260717-01:16:34,133 nipype.workflow INFO:
	 [Node] Finished "AAL116_sift_invnodevol_radius2_count",
elapsed time 0.824216s.
260717-01:16:35,880 nipype.workflow INFO:
	 [Job 0] Completed (mrtrix_atlasgraph.AAL116_sift_invnode
vol_radius2_count).
260717-01:16:35,882 nipype.workflow INFO:
	 [MultiProc] Running 0 tasks, and 4 jobs ready. Free memo
ry (GB): 56.51/56.51, Free processors: 4/4.
260717-01:16:35,958 nipype.workflow INFO:
	 [Node] Setting-up "mrtrix_atlasgraph.AAL116_radius2_mean
length" in "/home/jovyan/workspace/books/examples/diffusion_imaging/qsirecon-work/qsirecon_1_1_wf/su
b-CON01_mrtrix_multishell_msmt_noACT/sub_CON01_ses_preop_acq_AP_space_ACPC_desc_preproc_recon_wf/mrt
rix_conn/calc_connectivity/mrtrix_atlasgraph/AAL116_radius2_meanlength".
260717-01:16:35,960 nipype.workflow INFO:
	 [Node] Executing "AAL116_radius2_meanlength" <qsirecon.i
nterfaces.mrtrix.BuildConnectome>
260717-01:16:36,731 nipype.workflow INFO:
	 [Node] Finished "AAL116_radius2_meanlength", elapsed tim
e 0.769987s.
260717-01:16:37,882 nipype.workflow INFO:
	 [Job 1] Completed (mrtrix_atlasgraph.AAL116_radius2_mean
length).
260717-01:16:37,883 nipype.workflow INFO:
	 [MultiProc] Running 0 tasks, and 4 jobs ready. Free memo
ry (GB): 56.51/56.51, Free processors: 4/4.
260717-01:16:37,961 nipype.workflow INFO:
	 [Node] Setting-up "mrtrix_atlasgraph.AAL116_radius2_coun
t" in "/home/jovyan/workspace/books/examples/diffusion_imaging/qsirecon-work/qsirecon_1_1_wf/sub-CON
01_mrtrix_multishell_msmt_noACT/sub_CON01_ses_preop_acq_AP_space_ACPC_desc_preproc_recon_wf/mrtrix_c
onn/calc_connectivity/mrtrix_atlasgraph/AAL116_radius2_count".
260717-01:16:37,963 nipype.workflow INFO:
	 [Node] Executing "AAL116_radius2_count" <qsirecon.interf
aces.mrtrix.BuildConnectome>
260717-01:16:38,484 nipype.workflow INFO:
	 [Node] Finished "AAL116_radius2_count", elapsed time 0.5
20179s.
260717-01:16:39,884 nipype.workflow INFO:
	 [Job 2] Completed (mrtrix_atlasgraph.AAL116_radius2_coun
t).
260717-01:16:39,885 nipype.workflow INFO:
	 [MultiProc] Running 0 tasks, and 4 jobs ready. Free memo
ry (GB): 56.51/56.51, Free processors: 4/4.
260717-01:16:39,959 nipype.workflow INFO:
	 [Node] Setting-up "mrtrix_atlasgraph.AAL116_sift_radius2
_count" in "/home/jovyan/workspace/books/examples/diffusion_imaging/qsirecon-work/qsirecon_1_1_wf/su
b-CON01_mrtrix_multishell_msmt_noACT/sub_CON01_ses_preop_acq_AP_space_ACPC_desc_preproc_recon_wf/mrt
rix_conn/calc_connectivity/mrtrix_atlasgraph/AAL116_sift_radius2_count".
260717-01:16:39,961 nipype.workflow INFO:
	 [Node] Executing "AAL116_sift_radius2_count" <qsirecon.i
nterfaces.mrtrix.BuildConnectome>
260717-01:16:40,584 nipype.workflow INFO:
	 [Node] Finished "AAL116_sift_radius2_count", elapsed tim
e 0.622456s.
260717-01:16:41,886 nipype.workflow INFO:
	 [Job 3] Completed (mrtrix_atlasgraph.AAL116_sift_radius2
_count).
260717-01:16:41,887 nipype.workflow INFO:
	 [MultiProc] Running 0 tasks, and 6 jobs ready. Free memo
ry (GB): 56.51/56.51, Free processors: 4/4.
260717-01:16:41,963 nipype.workflow INFO:
	 [Node] Setting-up "mrtrix_atlasgraph.AAL116_sift_invnode
vol_radius2_count_c2t" in "/home/jovyan/workspace/books/examples/diffusion_imaging/qsirecon-work/qsi
recon_1_1_wf/sub-CON01_mrtrix_multishell_msmt_noACT/sub_CON01_ses_preop_acq_AP_space_ACPC_desc_prepr
oc_recon_wf/mrtrix_conn/calc_connectivity/mrtrix_atlasgraph/AAL116_sift_invnodevol_radius2_count_c2t
".
260717-01:16:41,965 nipype.workflow INFO:
	 [Node] Executing "AAL116_sift_invnodevol_radius2_count_c
2t" <qsirecon.interfaces.mrtrix.Connectome2Tck>
260717-01:16:43,811 nipype.workflow INFO:
	 [Node] Finished "AAL116_sift_invnodevol_radius2_count_c2
t", elapsed time 1.845405s.
260717-01:16:43,888 nipype.workflow INFO:
	 [Job 4] Completed (mrtrix_atlasgraph.AAL116_sift_invnode
vol_radius2_count_c2t).
260717-01:16:43,889 nipype.workflow INFO:
	 [MultiProc] Running 0 tasks, and 5 jobs ready. Free memo
ry (GB): 56.51/56.51, Free processors: 4/4.
260717-01:16:43,963 nipype.workflow INFO:
	 [Node] Setting-up "mrtrix_atlasgraph.AAL116_radius2_mean
length_c2t" in "/home/jovyan/workspace/books/examples/diffusion_imaging/qsirecon-work/qsirecon_1_1_w
f/sub-CON01_mrtrix_multishell_msmt_noACT/sub_CON01_ses_preop_acq_AP_space_ACPC_desc_preproc_recon_wf
/mrtrix_conn/calc_connectivity/mrtrix_atlasgraph/AAL116_radius2_meanlength_c2t".
260717-01:16:43,966 nipype.workflow INFO:
	 [Node] Executing "AAL116_radius2_meanlength_c2t" <qsirec
on.interfaces.mrtrix.Connectome2Tck>
260717-01:16:45,615 nipype.workflow INFO:
	 [Node] Finished "AAL116_radius2_meanlength_c2t", elapsed
 time 1.6486079999999999s.
260717-01:16:45,890 nipype.workflow INFO:
	 [Job 5] Completed (mrtrix_atlasgraph.AAL116_radius2_mean
length_c2t).
260717-01:16:45,891 nipype.workflow INFO:
	 [MultiProc] Running 0 tasks, and 4 jobs ready. Free memo
ry (GB): 56.51/56.51, Free processors: 4/4.
260717-01:16:45,965 nipype.workflow INFO:
	 [Node] Setting-up "mrtrix_atlasgraph.AAL116_radius2_coun
t_c2t" in "/home/jovyan/workspace/books/examples/diffusion_imaging/qsirecon-work/qsirecon_1_1_wf/sub
-CON01_mrtrix_multishell_msmt_noACT/sub_CON01_ses_preop_acq_AP_space_ACPC_desc_preproc_recon_wf/mrtr
ix_conn/calc_connectivity/mrtrix_atlasgraph/AAL116_radius2_count_c2t".
260717-01:16:45,969 nipype.workflow INFO:
	 [Node] Executing "AAL116_radius2_count_c2t" <qsirecon.in
terfaces.mrtrix.Connectome2Tck>
260717-01:16:47,596 nipype.workflow INFO:
	 [Node] Finished "AAL116_radius2_count_c2t", elapsed time
 1.6269390000000001s.
260717-01:16:47,892 nipype.workflow INFO:
	 [Job 6] Completed (mrtrix_atlasgraph.AAL116_radius2_coun
t_c2t).
260717-01:16:47,893 nipype.workflow INFO:
	 [MultiProc] Running 0 tasks, and 3 jobs ready. Free memo
ry (GB): 56.51/56.51, Free processors: 4/4.
260717-01:16:47,967 nipype.workflow INFO:
	 [Node] Setting-up "mrtrix_atlasgraph.AAL116_sift_radius2
_count_c2t" in "/home/jovyan/workspace/books/examples/diffusion_imaging/qsirecon-work/qsirecon_1_1_w
f/sub-CON01_mrtrix_multishell_msmt_noACT/sub_CON01_ses_preop_acq_AP_space_ACPC_desc_preproc_recon_wf
/mrtrix_conn/calc_connectivity/mrtrix_atlasgraph/AAL116_sift_radius2_count_c2t".
260717-01:16:47,970 nipype.workflow INFO:
	 [Node] Executing "AAL116_sift_radius2_count_c2t" <qsirec
on.interfaces.mrtrix.Connectome2Tck>
260717-01:16:49,594 nipype.workflow INFO:
	 [Node] Finished "AAL116_sift_radius2_count_c2t", elapsed
 time 1.623016s.
260717-01:16:49,894 nipype.workflow INFO:
	 [Job 7] Completed (mrtrix_atlasgraph.AAL116_sift_radius2
_count_c2t).
260717-01:16:49,895 nipype.workflow INFO:
	 [MultiProc] Running 0 tasks, and 4 jobs ready. Free memo
ry (GB): 56.51/56.51, Free processors: 4/4.
260717-01:16:49,968 nipype.workflow INFO:
	 [Node] Setting-up "mrtrix_atlasgraph.merge_mats" in "/ho
me/jovyan/workspace/books/examples/diffusion_imaging/qsirecon-work/qsirecon_1_1_wf/sub-CON01_mrtrix_
multishell_msmt_noACT/sub_CON01_ses_preop_acq_AP_space_ACPC_desc_preproc_recon_wf/mrtrix_conn/calc_c
onnectivity/mrtrix_atlasgraph/merge_mats".
260717-01:16:49,972 nipype.workflow INFO:
	 [Node] Executing "merge_mats" <nipype.interfaces.utility
.base.Merge>
260717-01:16:49,973 nipype.workflow INFO:
	 [Node] Finished "merge_mats", elapsed time 0.000155s.
260717-01:16:49,975 nipype.workflow INFO:
	 [Node] Setting-up "mrtrix_atlasgraph.merge_csvs" in "/ho
me/jovyan/workspace/books/examples/diffusion_imaging/qsirecon-work/qsirecon_1_1_wf/sub-CON01_mrtrix_
multishell_msmt_noACT/sub_CON01_ses_preop_acq_AP_space_ACPC_desc_preproc_recon_wf/mrtrix_conn/calc_c
onnectivity/mrtrix_atlasgraph/merge_csvs".
260717-01:16:49,978 nipype.workflow INFO:
	 [Node] Executing "merge_csvs" <nipype.interfaces.utility
.base.Merge>
260717-01:16:49,979 nipype.workflow INFO:
	 [Node] Finished "merge_csvs", elapsed time 0.00014s.
260717-01:16:49,980 nipype.workflow INFO:
	 [Node] Setting-up "mrtrix_atlasgraph.merge_tcks" in "/ho
me/jovyan/workspace/books/examples/diffusion_imaging/qsirecon-work/qsirecon_1_1_wf/sub-CON01_mrtrix_
multishell_msmt_noACT/sub_CON01_ses_preop_acq_AP_space_ACPC_desc_preproc_recon_wf/mrtrix_conn/calc_c
onnectivity/mrtrix_atlasgraph/merge_tcks".
260717-01:16:49,984 nipype.workflow INFO:
	 [Node] Executing "merge_tcks" <nipype.interfaces.utility
.base.Merge>
260717-01:16:49,985 nipype.workflow INFO:
	 [Node] Finished "merge_tcks", elapsed time 0.000126s.
260717-01:16:49,986 nipype.workflow INFO:
	 [Node] Setting-up "mrtrix_atlasgraph.merge_weights" in "
/home/jovyan/workspace/books/examples/diffusion_imaging/qsirecon-work/qsirecon_1_1_wf/sub-CON01_mrtr
ix_multishell_msmt_noACT/sub_CON01_ses_preop_acq_AP_space_ACPC_desc_preproc_recon_wf/mrtrix_conn/cal
c_connectivity/mrtrix_atlasgraph/merge_weights".
260717-01:16:49,990 nipype.workflow INFO:
	 [Node] Executing "merge_weights" <nipype.interfaces.util
ity.base.Merge>
260717-01:16:49,990 nipype.workflow INFO:
	 [Node] Finished "merge_weights", elapsed time 0.000126s.
260717-01:16:51,896 nipype.workflow INFO:
	 [Job 8] Completed (mrtrix_atlasgraph.merge_mats).
260717-01:16:51,897 nipype.workflow INFO:
	 [Job 9] Completed (mrtrix_atlasgraph.merge_csvs).
260717-01:16:51,897 nipype.workflow INFO:
	 [Job 10] Completed (mrtrix_atlasgraph.merge_tcks).
260717-01:16:51,898 nipype.workflow INFO:
	 [Job 11] Completed (mrtrix_atlasgraph.merge_weights).
260717-01:16:51,899 nipype.workflow INFO:
	 [MultiProc] Running 0 tasks, and 1 jobs ready. Free memo
ry (GB): 56.51/56.51, Free processors: 4/4.
260717-01:16:51,979 nipype.workflow INFO:
	 [Node] Setting-up "mrtrix_atlasgraph.merge_exemplars" in
 "/home/jovyan/workspace/books/examples/diffusion_imaging/qsirecon-work/qsirecon_1_1_wf/sub-CON01_mr
trix_multishell_msmt_noACT/sub_CON01_ses_preop_acq_AP_space_ACPC_desc_preproc_recon_wf/mrtrix_conn/c
alc_connectivity/mrtrix_atlasgraph/merge_exemplars".
260717-01:16:51,982 nipype.workflow INFO:
	 [Node] Executing "merge_exemplars" <nipype.interfaces.ut
ility.base.Merge>
260717-01:16:51,983 nipype.workflow INFO:
	 [Node] Finished "merge_exemplars", elapsed time 0.000156
s.
260717-01:16:53,898 nipype.workflow INFO:
	 [Job 12] Completed (mrtrix_atlasgraph.merge_exemplars).
260717-01:16:53,899 nipype.workflow INFO:
	 [MultiProc] Running 0 tasks, and 1 jobs ready. Free memo
ry (GB): 56.51/56.51, Free processors: 4/4.
260717-01:16:53,973 nipype.workflow INFO:
	 [Node] Setting-up "mrtrix_atlasgraph.compress_exemplars"
 in "/home/jovyan/workspace/books/examples/diffusion_imaging/qsirecon-work/qsirecon_1_1_wf/sub-CON01
_mrtrix_multishell_msmt_noACT/sub_CON01_ses_preop_acq_AP_space_ACPC_desc_preproc_recon_wf/mrtrix_con
n/calc_connectivity/mrtrix_atlasgraph/compress_exemplars".
260717-01:16:53,976 nipype.workflow INFO:
	 [Node] Executing "compress_exemplars" <qsirecon.interfac
es.mrtrix.CompressConnectome2Tck>
260717-01:16:54,845 nipype.workflow INFO:
	 [Node] Finished "compress_exemplars", elapsed time 0.867
641s.
260717-01:16:55,900 nipype.workflow INFO:
	 [Job 13] Completed (mrtrix_atlasgraph.compress_exemplars
).
260717-01:16:55,902 nipype.workflow INFO:
	 [MultiProc] Running 0 tasks, and 0 jobs ready. Free memo
ry (GB): 56.51/56.51, Free processors: 4/4.
260717-01:16:57,949 nipype.workflow INFO:
	 [Node] Setting-up "mrtrix_atlasgraph.compress_exemplars"
 in "/home/jovyan/workspace/books/examples/diffusion_imaging/qsirecon-work/qsirecon_1_1_wf/sub-CON01
_mrtrix_multishell_msmt_noACT/sub_CON01_ses_preop_acq_AP_space_ACPC_desc_preproc_recon_wf/mrtrix_con
n/calc_connectivity/mrtrix_atlasgraph/compress_exemplars".
260717-01:16:57,951 nipype.workflow INFO:
	 [Node] Cached "mrtrix_atlasgraph.compress_exemplars" - c
ollecting precomputed outputs
260717-01:16:57,951 nipype.workflow INFO:
	 [Node] "mrtrix_atlasgraph.
compress_exemplars" found cached.
260717-01:16:57,952 nipype.workflow INFO:
	 [Node] Finished "calc_
connectivity", elapsed time 30.101431s.
260717-01:16:59,650 nipype.workflow INFO:
	 [Node] Setting-up "qsirecon_1_1_wf.sub-CON01_mrtrix_mult
ishell_msmt_noACT.sub_CON01_ses_preop_acq_AP_space_ACPC_desc_preproc_recon_wf.mrtrix_conn.plot_conne
ctivity" in "/home/jovyan/workspace/books/examples/diffusion_imaging/qsirecon-work/qsirecon_1_1_wf/s
ub-CON01_mrtrix_multishell_msmt_noACT/sub_CON01_ses_preop_acq_AP_space_ACPC_desc_preproc_recon_wf/mr
trix_conn/plot_connectivity".
260717-01:16:59,655 nipype.workflow INFO:
	 [Node] Executing "plot_connectivity" <qsirecon.interface
s.reports.ConnectivityReport>
260717-01:16:59,905 nipype.workflow INFO:
	 [Node] Finished "plot_connectivity", elapsed time 0.2497
72s.
260717-01:17:03,571 nipype.workflow IMPORTANT:
	 QSIRecon finished successfully!
260717-01:17:03,575 nipype.workflow IMPORTANT:
	 Works derived from this QSIRecon execution should i
nclude the boilerplate text found in <OUTPUT_PATH>/logs/CITATION.md.
260717-01:17:03,610 nipype.utils WARNING:
	 DatasetType key not in /home/jovyan/workspace/books/exam
ples/diffusion_imaging/qsiprep-output/dataset_description.json. Assuming 'derivative'.
260717-01:17:04,735 nipype.utils WARNING:
	 DatasetType key not in /home/jovyan/workspace/books/exam
ples/diffusion_imaging/qsiprep-output/dataset_description.json. Assuming 'derivative'.
#remove the working dir
shutil.rmtree("qsirecon-work", ignore_errors=True)

QSIRecon outputs#

The reconstruction results are nested under derivatives/qsirecon-MRtrix3_act-None/ rather than sitting at the top level. The directory name comes from the qsirecon_suffix declared in the recon spec — a single run can emit several such datasets, so each is written as its own self-contained BIDS derivatives dataset, with act-None recording that we used the non-ACT variant.

Inside, sub-CON01/ses-preop/dwi/ holds the reconstruction proper: per-tissue FODs from MSMT-CSD (model-msmtcsd_param-fod_label-{WM,GM,CSF}, with the matching response functions as .txt), the mtnormalise outputs, the iFOD2 streamlines (model-ifod2_streamlines.tck.gz), the SIFT2 weights and proportionality coefficient (model-sift2_streamlineweights.csv, model-sift2_mu.txt), and the connectome itself in connectivity.mat. The figures/ directory holds the panels shown in the visual report, and sub-CON01_ses-preop.html is that report.

At the top level, atlases/ contains the AAL116 atlas as passed to --atlases, while the top-level sub-CON01/ses-preop/dwi/ holds it resampled into the subject’s ACPC space — the parcellation actually used to build the connectome.

! tree qsirecon-output/
qsirecon-output/
├── atlases
│   ├── atlas-AAL116
│   │   ├── atlas-AAL116_dseg.tsv
│   │   ├── atlas-AAL116_space-MNI152NLin2009cAsym_res-01_dseg.json
│   │   └── atlas-AAL116_space-MNI152NLin2009cAsym_res-01_dseg.nii.gz
│   └── dataset_description.json
├── dataset_description.json
├── derivatives
│   └── qsirecon-MRtrix3_act-None
│       ├── dataset_description.json
│       ├── logs
│       │   ├── CITATION.bib
│       │   ├── CITATION.html
│       │   ├── CITATION.md
│       │   └── CITATION.tex
│       ├── sub-CON01
│       │   └── ses-preop
│       │       ├── dwi
│       │       │   ├── sub-CON01_ses-preop_acq-AP_space-ACPC_connectivity.mat
│       │       │   ├── sub-CON01_ses-preop_acq-AP_space-ACPC_exemplarbundles.zip
│       │       │   ├── sub-CON01_ses-preop_acq-AP_space-ACPC_model-ifod2_streamlines.tck.gz
│       │       │   ├── sub-CON01_ses-preop_acq-AP_space-ACPC_model-msmtcsd_param-fod_label-CSF_dwimap.mif.gz
│       │       │   ├── sub-CON01_ses-preop_acq-AP_space-ACPC_model-msmtcsd_param-fod_label-CSF_dwimap.txt
│       │       │   ├── sub-CON01_ses-preop_acq-AP_space-ACPC_model-msmtcsd_param-fod_label-GM_dwimap.mif.gz
│       │       │   ├── sub-CON01_ses-preop_acq-AP_space-ACPC_model-msmtcsd_param-fod_label-GM_dwimap.txt
│       │       │   ├── sub-CON01_ses-preop_acq-AP_space-ACPC_model-msmtcsd_param-fod_label-WM_dwimap.mif.gz
│       │       │   ├── sub-CON01_ses-preop_acq-AP_space-ACPC_model-msmtcsd_param-fod_label-WM_dwimap.txt
│       │       │   ├── sub-CON01_ses-preop_acq-AP_space-ACPC_model-mtnorm_param-inliermask_dwimap.nii.gz
│       │       │   ├── sub-CON01_ses-preop_acq-AP_space-ACPC_model-mtnorm_param-norm_dwimap.nii.gz
│       │       │   ├── sub-CON01_ses-preop_acq-AP_space-ACPC_model-sift2_mu.txt
│       │       │   └── sub-CON01_ses-preop_acq-AP_space-ACPC_model-sift2_streamlineweights.csv
│       │       └── figures
│       │           ├── sub-CON01_ses-preop_acq-AP_space-ACPC_desc-MRtrix3Connectivity_matrices.svg
│       │           ├── sub-CON01_ses-preop_acq-AP_space-ACPC_desc-wmFOD_odfs.png
│       │           ├── sub-CON01_ses-preop_acq-AP_space-ACPC_desc-wmFOD_peaks.png
│       │           ├── sub-CON01_ses-preop_desc-about_T1w.html
│       │           └── sub-CON01_ses-preop_desc-summary_T1w.html
│       └── sub-CON01_ses-preop.html
├── logs
│   ├── CITATION.bib
│   ├── CITATION.html
│   ├── CITATION.md
│   └── CITATION.tex
└── sub-CON01
    ├── log
    │   └── 20260717-005045_82fbfcfd-1246-4f9c-b202-3760041c1194
    │       ├── qsirecon.toml
    │       └── recon_spec.yaml
    └── ses-preop
        └── dwi
            ├── sub-CON01_ses-preop_acq-AP_space-ACPC_seg-AAL116_dseg.mif.gz
            ├── sub-CON01_ses-preop_acq-AP_space-ACPC_seg-AAL116_dseg.nii.gz
            └── sub-CON01_ses-preop_acq-AP_space-ACPC_seg-AAL116_dseg.txt

16 directories, 38 files

3. Results#

We display the full QSIRecon visual report. It contains FOD peak/ODF visualisations and the connectome matrices figure, alongside run provenance and summary sections. The report references its figures as separate files, so we inline them (PNGs as base64, SVGs embedded directly) to make it render in the notebook.

# Display the QSIRecon HTML report with all images inlined.
# PNGs are base64-encoded; SVGs are embedded directly into the DOM.
def display_report(report_path):
    report_dir = os.path.dirname(report_path)
    with open(report_path) as f:
        soup = BeautifulSoup(f, 'html.parser')
    # Inline <img src=...> tags: PNG as base64, SVG embedded directly
    for img in soup.find_all('img'):
        src = img.get('src', '')
        if not src:
            continue
        img_path = os.path.join(report_dir, src.lstrip('./'))
        if os.path.exists(img_path):
            if src.endswith('.svg'):
                with open(img_path) as f:
                    svg_soup = BeautifulSoup(f.read(), 'html.parser')
                    svg_tag = svg_soup.find('svg')
                    if svg_tag:
                        img.replace_with(svg_tag)
            elif src.endswith('.png'):
                with open(img_path, 'rb') as f:
                    data = base64.b64encode(f.read()).decode()
                img['src'] = f'data:image/png;base64,{data}'
    # Also inline SVGs referenced in <a href> tags
    for tag in soup.find_all(href=lambda h: h and h.endswith('.svg')):
        svg_path = os.path.join(report_dir, tag['href'])
        if os.path.exists(svg_path):
            with open(svg_path) as f:
                svg_soup = BeautifulSoup(f.read(), 'html.parser')
                tag.replace_with(svg_soup)
    # Remove nav/button clutter
    for tag in soup(['button', 'nav', 'head']):
        tag.decompose()
    display(HTML(str(soup)))
display_report('./qsirecon-output/derivatives/qsirecon-MRtrix3_act-None/sub-CON01_ses-preop.html')

Summary

  • Subject ID: CON01
  • Structural images: 1 T1-weighted
  • Diffusion-weighted series: 1
  • Standard output spaces: MNI152NLin2009cAsym
  • Non-standard output spaces:
  • FreeSurfer reconstruction: Pre-existing directory

MRtrix3

Reports for: session preop, acquisition AP.

Constrained Spherical Deconvolution

Directionally color-coded FOD peaks overlaid on the b=0 reference image.

Get figure file: sub-CON01/ses-preop/figures/sub-CON01_ses-preop_acq-AP_space-ACPC_desc-wmFOD_peaks.png

Constrained Spherical Deconvolution

Three views of ODFs in ROIs.

Get figure file: sub-CON01/ses-preop/figures/sub-CON01_ses-preop_acq-AP_space-ACPC_desc-wmFOD_odfs.png

MRtrix3 Connectivity

Connectivity estimated by tck2connectome.

2026-07-17T01:16:59.863613 image/svg+xml Matplotlib v3.8.3, https://matplotlib.org/
Get figure file: 2026-07-17T01:16:59.863613 image/svg+xml Matplotlib v3.8.3, https://matplotlib.org/

About

  • QSIRecon version: 1.1.1.dev0+gaf43da9.d20250414
  • QSIRecon command: /opt/conda/envs/qsiprep/bin/qsirecon qsiprep-output qsirecon-output participant --participant-label CON01 --recon-spec recon_spec_ci.yaml --fs-license-file /home/jovyan/.license --atlases AAL116 -w qsirecon-work --nthreads 12 --omp-nthreads 4 --mem-mb 48225
  • Date postprocessed: 2026-07-17 00:51:21 +0000

Methods

We kindly ask to report results preprocessed with this tool using the following boilerplate.

Reconstruction was performed using QSIRecon 1.1.1.dev0+gaf43da9.d20250414 (Cieslak et al. (2021)), which is based on Nipype 1.9.1 (Gorgolewski et al. (2011); Gorgolewski et al. (2018); RRID:SCR_002502).

Anatomical data for DWI reconstruction

T1w-based spatial normalization calculated during preprocessing was used to map atlases from template space into alignment with DWIs. Brain masks from antsBrainExtraction were used in all subsequent reconstruction steps. The following atlases were used in the workflow: the Automated Anatomical Labeling (AAL) 116-parcel atlas (Tzourio-Mazoyer et al. 2002). Cortical parcellations were mapped from template space to DWIS using the T1w-based spatial normalization.

MRtrix3 Reconstruction

Multi-tissue fiber response functions were estimated using the dhollander algorithm. FODs were estimated via constrained spherical deconvolution (CSD, Tournier et al. (2004), Tournier et al. (2008)) using an unsupervised multi-tissue method (Dhollander et al. (2019), Dhollander, Raffelt, and Connelly (2016)). Reconstruction was done using MRtrix3 (J-Donald et al. (2019)). FODs were intensity-normalized using mtnormalize (Raffelt et al. (2017)).

Many internal operations of QSIRecon use Nilearn 0.10.1 (Abraham et al. 2014, RRID:SCR_001362) and Dipy 1.8.0 (Garyfallidis et al. 2014). For more details of the pipeline, see the section corresponding to workflows in QSIRecon’s documentation.

References

Abraham, Alexandre, Fabian Pedregosa, Michael Eickenberg, Philippe Gervais, Andreas Mueller, Jean Kossaifi, Alexandre Gramfort, Bertrand Thirion, and Gael Varoquaux. 2014. “Machine Learning for Neuroimaging with Scikit-Learn.” Frontiers in Neuroinformatics 8. https://doi.org/10.3389/fninf.2014.00014.

Cieslak, Matthew, Philip A Cook, Xiaosong He, Fang-Cheng Yeh, Thijs Dhollander, Azeez Adebimpe, Geoffrey K Aguirre, et al. 2021. “QSIPrep: An Integrative Platform for Preprocessing and Reconstructing Diffusion Mri Data.” Nature Methods 18 (7). Nature Publishing Group US New York: 775–78. https://doi.org/10.1038/s41592-021-01185-5.

Dhollander, Thijs, David Raffelt, and Alan Connelly. 2016. “Unsupervised 3-Tissue Response Function Estimation from Single-Shell or Multi-Shell Diffusion Mr Data Without a Co-Registered T1 Image.” In ISMRM Workshop on Breaking the Barriers of Diffusion Mri, 5:5.

Dhollander, T, R Mito, D Raffelt, and A Connelly. 2019. “Improved White Matter Response Function Estimation for 3-Tissue Constrained Spherical Deconvolution.” In Proc. Intl. Soc. Mag. Reson. Med, 555.

Garyfallidis, Eleftherios, Matthew Brett, Bagrat Amirbekian, Ariel Rokem, Stefan Van Der Walt, Maxime Descoteaux, and Ian Nimmo-Smith. 2014. “Dipy, a Library for the Analysis of Diffusion Mri Data.” Frontiers in Neuroinformatics 8. Frontiers: 8.

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Reconstruction was
performed using *QSIRecon* 1.1.1.dev0+gaf43da9.d20250414 (@cieslak2021qsiprep),
which is based on *Nipype* 1.9.1
(@nipype1; @nipype2; RRID:SCR_002502).



#### Anatomical data for DWI reconstruction

T1w-based spatial normalization calculated during preprocessing was used to map atlases from template space into alignment with DWIs. Brain masks from antsBrainExtraction were used in all subsequent reconstruction steps. The following atlases were used in the workflow: the Automated Anatomical Labeling (AAL) 116-parcel atlas [@tzourio2002automated]. Cortical parcellations were mapped from template space to DWIS using the T1w-based spatial normalization. 


#### MRtrix3 Reconstruction

Multi-tissue fiber response functions were estimated using the dhollander algorithm. 
FODs were estimated via constrained spherical deconvolution 
(CSD, @originalcsd, @tournier2008csd) using an unsupervised multi-tissue method (@dhollander2019response, @dhollander2016unsupervised). Reconstruction was done using MRtrix3 (@mrtrix3). FODs were intensity-normalized using mtnormalize (@mtnormalize).

Many internal operations of *QSIRecon* use
*Nilearn* 0.10.1 [@nilearn, RRID:SCR_001362] and
*Dipy* 1.8.0 [@dipy].
For more details of the pipeline, see [the section corresponding
to workflows in *QSIRecon*'s documentation](https://qsirecon.readthedocs.io/en/latest/workflows.html).


### References

    
Reconstruction was performed using \emph{QSIRecon}
1.1.1.dev0+gaf43da9.d20250414 (\citet{cieslak2021qsiprep}), which is
based on \emph{Nipype} 1.9.1 (\citet{nipype1}; \citet{nipype2};
RRID:SCR\_002502).

\hypertarget{anatomical-data-for-dwi-reconstruction}{%
\paragraph{Anatomical data for DWI
reconstruction}\label{anatomical-data-for-dwi-reconstruction}}

T1w-based spatial normalization calculated during preprocessing was used
to map atlases from template space into alignment with DWIs. Brain masks
from antsBrainExtraction were used in all subsequent reconstruction
steps. The following atlases were used in the workflow: the Automated
Anatomical Labeling (AAL) 116-parcel atlas \citep{tzourio2002automated}.
Cortical parcellations were mapped from template space to DWIS using the
T1w-based spatial normalization.

\hypertarget{mrtrix3-reconstruction}{%
\paragraph{MRtrix3 Reconstruction}\label{mrtrix3-reconstruction}}

Multi-tissue fiber response functions were estimated using the
dhollander algorithm. FODs were estimated via constrained spherical
deconvolution (CSD, \citet{originalcsd}, \citet{tournier2008csd}) using
an unsupervised multi-tissue method (\citet{dhollander2019response},
\citet{dhollander2016unsupervised}). Reconstruction was done using
MRtrix3 (\citet{mrtrix3}). FODs were intensity-normalized using
mtnormalize (\citet{mtnormalize}).

Many internal operations of \emph{QSIRecon} use \emph{Nilearn} 0.10.1
\citep[RRID:SCR\_001362]{nilearn} and \emph{Dipy} 1.8.0 \citep{dipy}.
For more details of the pipeline, see
\href{https://qsirecon.readthedocs.io/en/latest/workflows.html}{the
section corresponding to workflows in \emph{QSIRecon}'s documentation}.

\hypertarget{references}{%
\subsubsection{References}\label{references}}

\bibliography{/home/jovyan/workspace/books/examples/diffusion\_imaging/qsirecon-output/logs/CITATION.bib}

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  publisher={Elsevier}
}

@article{dwidenoise2,
  title={Diffusion MRI noise mapping using random matrix theory},
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  pages={1582--1593},
  year={2016},
  publisher={Wiley Online Library}
}

@article{merlet3dshore,
  title={Continuous diffusion signal, EAP and ODF estimation via compressive sensing in diffusion MRI},
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  publisher={Elsevier}
}

@article{pncprocessing,
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  publisher={Elsevier}
}

@inproceedings{dhollander2019response,
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  pages={555},
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}

@inproceedings{dhollander2016novel,
  title={A novel iterative approach to reap the benefits of multi-tissue CSD from just single-shell (+ b= 0) diffusion MRI data},
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  year={2016}
}

@inproceedings{dhollander2016unsupervised,
  title={Unsupervised 3-tissue response function estimation from single-shell or multi-shell diffusion MR data without a co-registered T1 image},
  author={Dhollander, Thijs and Raffelt, David and Connelly, Alan},
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}

@article{msmt5tt,
  title={Multi-tissue constrained spherical deconvolution for improved analysis of multi-shell diffusion MRI data},
  author={Jeurissen, Ben and Tournier, Jacques-Donald and Dhollander, Thijs and Connelly, Alan and Sijbers, Jan},
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}

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}

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  publisher={Elsevier}
}

@inproceedings{mtnormalize,
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  author={Raffelt, David and Dhollander, Thijs and Tournier, J-Donald and Tabbara, Rami and Smith, Robert E and Pierre, Eric and Connelly, Alan},
  booktitle={Proc. Intl. Soc. Mag. Reson. Med},
  volume={25},
  pages={3541},
  year={2017}
}

@article{yeh2010gqi,
  title={Generalized $q$-sampling imaging},
  author={Yeh, Fang-Cheng and Wedeen, Van Jay and Tseng, Wen-Yih Isaac},
  journal={IEEE transactions on medical imaging},
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  number={9},
  pages={1626--1635},
  year={2010},
  publisher={IEEE}
}

@article{anderssoneddy,
  title={An integrated approach to correction for off-resonance effects and subject movement in diffusion MR imaging},
  author={Andersson, Jesper LR and Sotiropoulos, Stamatios N},
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  volume={125},
  pages={1063--1078},
  year={2016},
  publisher={Elsevier}
}

@article{eddyrepol,
  title={Incorporating outlier detection and replacement into a non-parametric framework for movement and distortion correction of diffusion MR images},
  author={Andersson, Jesper LR and Graham, Mark S and Zsoldos, Enik{\H{o}} and Sotiropoulos, Stamatios N},
  journal={Neuroimage},
  volume={141},
  pages={556--572},
  year={2016},
  publisher={Elsevier}
}

@article{fsllsr,
  title={How to correct susceptibility distortions in spin-echo echo-planar images: application to diffusion tensor imaging},
  author={Andersson, Jesper LR and Skare, Stefan and Ashburner, John},
  journal={Neuroimage},
  volume={20},
  number={2},
  pages={870--888},
  year={2003},
  publisher={Elsevier}
}


@article{eddysus,
  title={Susceptibility-induced distortion that varies due to motion: correction in diffusion MR without acquiring additional data},
  author={Andersson, Jesper LR and Graham, Mark S and Drobnjak, Ivana and Zhang, Hui and Campbell, Jon},
  journal={Neuroimage},
  volume={171},
  pages={277--295},
  year={2018},
  publisher={Elsevier}
}

@article{eddys2v,
  title={Towards a comprehensive framework for movement and distortion correction of diffusion MR images: Within volume movement},
  author={Andersson, Jesper LR and Graham, Mark S and Drobnjak, Ivana and Zhang, Hui and Filippini, Nicola and Bastiani, Matteo},
  journal={Neuroimage},
  volume={152},
  pages={450--466},
  year={2017},
  publisher={Elsevier}
}

@article{topup,
  title={How to correct susceptibility distortions in spin-echo echo-planar images: application to diffusion tensor imaging},
  author={Andersson, Jesper LR and Skare, Stefan and Ashburner, John},
  journal={Neuroimage},
  volume={20},
  number={2},
  pages={870--888},
  year={2003},
  publisher={Elsevier}
}

@article{mrdegibbs,
  title={Gibbs-ringing artifact removal based on local subvoxel-shifts},
  author={Kellner, Elias and Dhital, Bibek and Kiselev, Valerij G and Reisert, Marco},
  journal={Magnetic resonance in medicine},
  volume={76},
  number={5},
  pages={1574--1581},
  year={2016},
  publisher={Wiley Online Library}
}

@article{patch2self,
  title={Patch2Self: Denoising Diffusion MRI with Self-Supervised Learning​},
  author={Fadnavis, Shreyas and Batson, Joshua and Garyfallidis, Eleftherios},
  journal={Advances in Neural Information Processing Systems},
  volume={33},
  year={2020}
}

@article{noddi,
  title={NODDI: practical in vivo neurite orientation dispersion and density imaging of the human brain},
  author={Zhang, Hui and Schneider, Torben and Wheeler-Kingshott, Claudia A and Alexander, Daniel C},
  journal={Neuroimage},
  volume={61},
  number={4},
  pages={1000--1016},
  year={2012},
  publisher={Elsevier}
}

@article{amico,
  title={Accelerated microstructure imaging via convex optimization (AMICO) from diffusion MRI data},
  author={Daducci, Alessandro and Canales-Rodr{\'\i}guez, Erick J and Zhang, Hui and Dyrby, Tim B and Alexander, Daniel C and Thiran, Jean-Philippe},
  journal={NeuroImage},
  volume={105},
  pages={32--44},
  year={2015},
  publisher={Elsevier}
}

@article{drbuddi,
  title={DR-BUDDI (Diffeomorphic Registration for Blip-Up blip-Down Diffusion Imaging) method for correcting echo planar imaging distortions},
  author={Irfanoglu, M Okan and Modi, Pooja and Nayak, Amritha and Hutchinson, Elizabeth B and Sarlls, Joelle and Pierpaoli, Carlo},
  journal={Neuroimage},
  volume={106},
  pages={284--299},
  year={2015},
  publisher={Elsevier}
}

@inproceedings{tortoisev3,
  title={TORTOISE v3: Improvements and new features of the NIH diffusion MRI processing pipeline},
  author={Irfanoglu, Mustafa Okan and Nayak, Amritha and Jenkins, Jeffrey and Pierpaoli, Carlo},
  booktitle={Program and proceedings of the ISMRM 25th annual meeting and exhibition, Honolulu, HI, USA},
  year={2017}
}

@article{pfgibbs,
  title={Removal of partial Fourier-induced Gibbs (RPG) ringing artifacts in MRI},
  author={Lee, Hong-Hsi and Novikov, Dmitry S and Fieremans, Els},
  journal={Magnetic Resonance in Medicine},
  volume={86},
  number={5},
  pages={2733--2750},
  year={2021},
  publisher={Wiley Online Library}
}

@article{synthstrip,
  title={SynthStrip: skull-stripping for any brain image},
  author={Hoopes, Andrew and Mora, Jocelyn S and Dalca, Adrian V and Fischl, Bruce and Hoffmann, Malte},
  journal={NeuroImage},
  volume={260},
  pages={119474},
  year={2022},
  publisher={Elsevier}
}

@article{synthseg1,
  title={SynthSeg: Segmentation of brain MRI scans of any contrast and resolution without retraining},
  author={Billot, Benjamin and Greve, Douglas N and Puonti, Oula and Thielscher, Axel and Van Leemput, Koen and Fischl, Bruce and Dalca, Adrian V and Iglesias, Juan Eugenio and others},
  journal={Medical image analysis},
  volume={86},
  pages={102789},
  year={2023},
  publisher={Elsevier}
}

@article{synthseg2,
  title={Robust machine learning segmentation for large-scale analysis of heterogeneous clinical brain MRI datasets},
  author={Billot, Benjamin and Magdamo, Colin and Cheng, You and Arnold, Steven E and Das, Sudeshna and Iglesias, Juan Eugenio},
  journal={Proceedings of the National Academy of Sciences},
  volume={120},
  number={9},
  pages={e2216399120},
  year={2023},
  publisher={National Acad Sciences}
}

@article{yeh2013deterministic,
  title={Deterministic diffusion fiber tracking improved by quantitative anisotropy},
  author={Yeh, Fang-Cheng and Verstynen, Timothy D and Wang, Yibao and Fern{\'a}ndez-Miranda, Juan C and Tseng, Wen-Yih Isaac},
  journal={PloS one},
  volume={8},
  number={11},
  pages={e80713},
  year={2013},
  publisher={Public Library of Science San Francisco, USA}
}

@article{autotrack,
  title={Shape analysis of the human association pathways},
  author={Yeh, Fang-Cheng},
  journal={Neuroimage},
  volume={223},
  pages={117329},
  year={2020},
  publisher={Elsevier}
}

@article{smith2012anatomically,
  title={Anatomically-constrained tractography: improved diffusion MRI streamlines tractography through effective use of anatomical information},
  author={Smith, Robert E and Tournier, Jacques-Donald and Calamante, Fernando and Connelly, Alan},
  journal={Neuroimage},
  volume={62},
  number={3},
  pages={1924--1938},
  year={2012},
  publisher={Elsevier},
  url={https://doi.org/10.1016/j.neuroimage.2012.06.005},
  doi={10.1016/j.neuroimage.2012.06.005}
}

@article{smith2015sift2,
  title={SIFT2: Enabling dense quantitative assessment of brain white matter connectivity using streamlines tractography},
  author={Smith, Robert E and Tournier, Jacques-Donald and Calamante, Fernando and Connelly, Alan},
  journal={Neuroimage},
  volume={119},
  pages={338--351},
  year={2015},
  publisher={Elsevier},
  url={https://doi.org/10.1016/j.neuroimage.2015.06.092},
  doi={10.1016/j.neuroimage.2015.06.092}
}

@article{yeh2022population,
  title={Population-based tract-to-region connectome of the human brain and its hierarchical topology},
  author={Yeh, Fang-Cheng},
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  volume={13},
  number={1},
  pages={4933},
  year={2022},
  publisher={Nature Publishing Group UK London},
  url={https://doi.org/10.1038/s41467-022-32595-4},
  doi={10.1038/s41467-022-32595-4}
}

@article{schaefer2018local,
  title={Local-global parcellation of the human cerebral cortex from intrinsic functional connectivity MRI},
  author={Schaefer, Alexander and Kong, Ru and Gordon, Evan M and Laumann, Timothy O and Zuo, Xi-Nian and Holmes, Avram J and Eickhoff, Simon B and Yeo, BT Thomas},
  journal={Cerebral cortex},
  volume={28},
  number={9},
  pages={3095--3114},
  year={2018},
  publisher={Oxford University Press},
  url={https://doi.org/10.1093/cercor/bhx179},
  doi={10.1093/cercor/bhx179}
}

@article{yeo2011organization,
  title={The organization of the human cerebral cortex estimated by intrinsic functional connectivity},
  author={Yeo, BT Thomas and Krienen, Fenna M and Sepulcre, Jorge and Sabuncu, Mert R and Lashkari, Danial and Hollinshead, Marisa and Roffman, Joshua L and Smoller, Jordan W and Z{\"o}llei, Lilla and Polimeni, Jonathan R and others},
  journal={Journal of neurophysiology},
  year={2011},
  publisher={American Physiological Society Bethesda, MD},
  url={https://doi.org/10.1152/jn.00338.2011},
  doi={10.1152/jn.00338.2011}
}

@article{joliot2015aicha,
  title={AICHA: An atlas of intrinsic connectivity of homotopic areas},
  author={Joliot, Marc and Jobard, Ga{\"e}l and Naveau, Mika{\"e}l and Delcroix, Nicolas and Petit, Laurent and Zago, Laure and Crivello, Fabrice and Mellet, Emmanuel and Mazoyer, Bernard and Tzourio-Mazoyer, Nathalie},
  journal={Journal of neuroscience methods},
  volume={254},
  pages={46--59},
  year={2015},
  publisher={Elsevier},
  url={https://doi.org/10.1016/j.jneumeth.2015.07.013},
  doi={10.1016/j.jneumeth.2015.07.013}
}

@article{fan2016human,
  title={The human brainnetome atlas: a new brain atlas based on connectional architecture},
  author={Fan, Lingzhong and Li, Hai and Zhuo, Junjie and Zhang, Yu and Wang, Jiaojian and Chen, Liangfu and Yang, Zhengyi and Chu, Congying and Xie, Sangma and Laird, Angela R and others},
  journal={Cerebral cortex},
  volume={26},
  number={8},
  pages={3508--3526},
  year={2016},
  publisher={Oxford University Press},
  url={https://doi.org/10.1093/cercor/bhw157},
  doi={10.1093/cercor/bhw157}
}

@article{gordon2016generation,
  title={Generation and evaluation of a cortical area parcellation from resting-state correlations},
  author={Gordon, Evan M and Laumann, Timothy O and Adeyemo, Babatunde and Huckins, Jeremy F and Kelley, William M and Petersen, Steven E},
  journal={Cerebral cortex},
  volume={26},
  number={1},
  pages={288--303},
  year={2016},
  publisher={Oxford University Press},
  url={https://doi.org/10.1093/cercor/bhu239},
  doi={10.1093/cercor/bhu239}
}

@article{tzourio2002automated,
  title={Automated anatomical labeling of activations in SPM using a macroscopic anatomical parcellation of the MNI MRI single-subject brain},
  author={Tzourio-Mazoyer, Nathalie and Landeau, Brigitte and Papathanassiou, Dimitri and Crivello, Fabrice and Etard, Octave and Delcroix, Nicolas and Mazoyer, Bernard and Joliot, Marc},
  journal={Neuroimage},
  volume={15},
  number={1},
  pages={273--289},
  year={2002},
  publisher={Elsevier},
  url={https://doi.org/10.1006/nimg.2001.0978},
  doi={10.1006/nimg.2001.0978}
}

@article{smith2020hybrid,
  title={Hybrid surface-volume segmentation for improved anatomically-constrained tractography},
  author={Smith, Robert and Skoch, Antonin and Bajada, Claude J and Caspers, Svenja and Connelly, Alan},
  year={2020},
  publisher={OHBM},
  journal={OHBM},
  url={https://www.um.edu.mt/library/oar/handle/123456789/59839}
}

@article{pauli2018high,
  title={A high-resolution probabilistic in vivo atlas of human subcortical brain nuclei},
  author={Pauli, Wolfgang M and Nili, Amanda N and Tyszka, J Michael},
  journal={Scientific data},
  volume={5},
  number={1},
  pages={1--13},
  year={2018},
  publisher={Nature Publishing Group},
  url={https://doi.org/10.1038/sdata.2018.63},
  doi={10.1038/sdata.2018.63}
}


@article{king2019functional,
  title={Functional boundaries in the human cerebellum revealed by a multi-domain task battery},
  author={King, Maedbh and Hernandez-Castillo, Carlos R and Poldrack, Russell A and Ivry, Richard B and Diedrichsen, J{\"o}rn},
  journal={Nature neuroscience},
  volume={22},
  number={8},
  pages={1371--1378},
  year={2019},
  publisher={Nature Publishing Group US New York},
  url={https://doi.org/10.1038/s41593-019-0436-x},
  doi={10.1038/s41593-019-0436-x}
}

@article{najdenovska2018vivo,
  title={In-vivo probabilistic atlas of human thalamic nuclei based on diffusion-weighted magnetic resonance imaging},
  author={Najdenovska, Elena and Alem{\'a}n-G{\'o}mez, Yasser and Battistella, Giovanni and Descoteaux, Maxime and Hagmann, Patric and Jacquemont, Sebastien and Maeder, Philippe and Thiran, Jean-Philippe and Fornari, Eleonora and Bach Cuadra, Meritxell},
  journal={Scientific data},
  volume={5},
  number={1},
  pages={1--11},
  year={2018},
  publisher={Nature Publishing Group},
  url={https://doi.org/10.1038/sdata.2018.270},
  doi={10.1038/sdata.2018.270}
}

@article{parker2021not,
title = {Not all voxels are created equal: Reducing estimation bias in regional NODDI metrics using tissue-weighted means},
journal = {NeuroImage},
volume = {245},
pages = {118749},
year = {2021},
issn = {1053-8119},
doi = {https://doi.org/10.1016/j.neuroimage.2021.118749},
url = {https://www.sciencedirect.com/science/article/pii/S1053811921010211},
author = {C.S. Parker and T. Veale and M. Bocchetta and C.F. Slattery and I.B. Malone and D.L. Thomas and J.M. Schott and D.M. Cash and H. Zhang},
keywords = {Diffusion MRI, Microstructure imaging, Region-of-interest, Arithmetic mean, Tissue-weighted mean},
abstract = {Neurite orientation dispersion and density imaging (NODDI) estimates microstructural properties of brain tissue relating to the organisation and processing capacity of neurites, which are essential elements for neuronal communication. Descriptive statistics of NODDI tissue metrics are commonly analyzed in regions-of-interest (ROI) to identify brain-phenotype associations. Here, the conventional method to calculate the ROI mean weights all voxels equally. However, this produces biased estimates in the presence of CSF partial volume. This study introduces the tissue-weighted mean, which calculates the mean NODDI metric across the tissue within an ROI, utilising the tissue fraction estimate from NODDI to reduce estimation bias. We demonstrate the proposed mean in a study of white matter abnormalities in young onset Alzheimer's disease (YOAD). Results show the conventional mean induces significant bias that correlates with CSF partial volume, primarily affecting periventricular regions and more so in YOAD subjects than in healthy controls. Due to the differential extent of bias between healthy controls and YOAD subjects, the conventional mean under- or over-estimated the effect size for group differences in many ROIs. This demonstrates the importance of using the correct estimation procedure when inferring group differences in studies where the extent of CSF partial volume differs between groups. These findings are robust across different acquisition and processing conditions. Bias persists in ROIs at higher image resolution, as demonstrated using data obtained from the third phase of the Alzheimer's disease neuroimaging initiative (ADNI); and when performing ROI analysis in template space. This suggests that conventional ROI means of NODDI metrics are biased estimates under most contemporary experimental conditions, the correction of which requires the proposed tissue-weighted mean. The tissue-weighted mean produces accurate estimates of ROI means and group differences when ROIs contain voxels with CSF partial volume. In addition to NODDI, the technique can be applied to other multi-compartment models that account for CSF partial volume, such as the free water elimination method. We expect the technique to help generate new insights into normal and abnormal variation in tissue microstructure of regions typically confounded by CSF partial volume, such as those in individuals with larger ventricles due to atrophy associated with neurodegenerative disease.}
}

Errors

Dependencies in Jupyter/Python#

  • Using the package watermark to document system environment and software versions used in this notebook, alongside the Neurodesktop version extracted from the JUPYTER_IMAGE or NEURODESKTOP_VERSION environment variables.

import os

%load_ext watermark

%watermark
%watermark --iversions

neurodesktop_version = (
    os.environ.get('JUPYTER_IMAGE', '').split(':')[-1] or
    os.environ.get('NEURODESKTOP_VERSION', 'unknown')
)

print(f"Neurodesktop version: {neurodesktop_version}")
Last updated: 2026-07-17T01:17:06.190339+00:00

Python implementation: CPython
Python version       : 3.13.14
IPython version      : 9.12.0

Compiler    : GCC 14.3.0
OS          : Linux
Release     : 6.8.0-111-generic
Machine     : x86_64
Processor   : x86_64
CPU cores   : 16
Architecture: 64bit

IPython   : 9.12.0
bs4       : 4.15.0
matplotlib: 3.11.0
numpy     : 2.5.1

Neurodesktop version: 2026-07-11