Multi-component neonatal diffusion MRI atlas created for the publication

Pietsch, Maximilian, et al. "A framework for multi-component analysis of diffusion MRI data over the neonatal period". NeuroImage 186 (2019): 321-337.
https://doi.org/10.1016/j.neuroimage.2018.10.060

Maximilian Pietsch bd800c9242 update headers order 3 months ago
v1 21544d0a92 gin commit from perinatal117-pc 3 months ago
LICENSE 013a0add8b Initial commit 3 months ago
README.md bd800c9242 update headers order 3 months ago
components.png 36b535a8c9 repo setup 3 months ago
datacite.yml 5cb998749f update description 3 months ago

README.md

tracking performed on the A0 component overlaid onto the tissue component ODFs

dHCP neonatal-multi-component-HARDI-atlas

This hosts the multi-component atlas of diffusion MRI data over the neonatal period created for the publication A framework for multi-component analysis of diffusion MRI data over the neonatal period. doi: 10.1016/j.neuroimage.2018.10.060 using data collected as part of the developing Human Connectome Project (dHCP).


Cite

Please cite the following publication:

Pietsch, Maximilian, et al. "A framework for multi-component analysis of diffusion MRI data over the neonatal period." NeuroImage 186 (2019): 321-337.

@article{pietsch2019framework,
  title={A framework for multi-component analysis of diffusion MRI data over the neonatal period},
  author={Pietsch, Maximilian and Christiaens, Daan and Hutter, Jana and Cordero-Grande, Lucilio and Price, Anthony N and Hughes, Emer and Edwards, A David and Hajnal, Joseph V and Counsell, Serena J and Tournier, J-Donald},
  journal={NeuroImage},
  volume={186},
  pages={321--337},
  year={2019},
  publisher={Elsevier}
}

Download

Manually

The weekly templates can be downloaded individually from here.

via the GIN command line interface

This describes how to download the data using the GIN-CLI client.

On macOS, it can be installed via homebrew:

brew tap g-node/pkg
brew install g-node/pkg/gin-cli

On ubuntu:

wget https://web.gin.g-node.org/G-Node/gin-cli-releases/raw/master/gin-cli-latest.deb
sudo dpkg -i gin-cli-latest.deb
sudo apt install -f

For standlone binaries and instructions for other operating systems, see here.

Then, to download this repository simply execute

gin get maxpietsch/dHCP_neonatal_HARDI_atlas
cd dHCP_neonatal_HARDI_atlas

Initially, place-holder files are downloaded instead of larger files (.git/annex). If you want to download all files use gin download --content, for individual files or directories use gin get-content <location>, for downloading all rigidly aligned templates use gin get-content v1/rigid/mean, check the download status with gin ls. See GIN CLI Usage Tutorial for details.

via Datalad

If needed, install datalad, then clone this repo with

datalad clone https://gin.g-node.org/maxpietsch/dHCP_neonatal_HARDI_atlas
cd dHCP_neonatal_HARDI_atlas

Finally, download any files needed. For instance, the group-average templates can be downloaded via datalad get v1/rigid/mean.

Data

Response functions and .mif.gz images can be processed, converted and inspected with MRtrix3 (https://www.mrtrix.org/).

Note that mean and median aggregation was perfomed using (Not-a-Number-) masked data using the brain masks as inclusion criteria for the aggregation operation. This prevents bias due to cropped data and allows retrospectively thresholding the template voxels by the number of subjects using the count.mif.gz images. For instance, the following MRtrix3 command replaces voxel values to which fewer than 5 subjects contribute by NaNs: mrcalc count.mif.gz 5 -ge odf_o_normed_cyo.mif.gz nan -if odf_o_normed_cyo_thresholded.mif.gz

Organisation

This repo is organised hierarchically:

├── LICENSE
├── README.md
└── v1                          <-- atlas version (`v1` is as used for the paper)
    ├── joint                   <-- jointly aligned data (single space across time)
    │   ├── mean                <-- mode of aggregation
    │   ├── median              <-- mode of aggregation
    │   ├── rois                <-- regions of interest used for the paper
    ├── rigid                   <-- weekly templates, rigidly aligned
    │   ├── mean
    │   └── median
    └── metadata                <-- subject information and response functions
        ├── rf_csf_all
        ├── rf_native
        ├── rf_tissue_32.9
        ├── rf_tissue_44.1
        ├── sub_ses_ga_32.9
        ├── sub_ses_ga_34.0
        ├── sub_ses_ga_35.2
        ├── sub_ses_ga_35.7
        ├── sub_ses_ga_37.1
        ├── sub_ses_ga_38.1
        ├── sub_ses_ga_39.1
        ├── sub_ses_ga_40.1
        ├── sub_ses_ga_40.9
        ├── sub_ses_ga_42.0
        ├── sub_ses_ga_42.8
        └── sub_ses_ga_44.1

The files (see fig. 3):


├── LICENSE
├── README.md
└── v1
    ├── joint
    │   ├── mean
    │   │   ├── 32.9
    │   │   │   ├── adc.mif.gz                         <-- DTI-fit, ADC map
    │   │   │   ├── count.mif.gz                       <-- sum across masks, useful to modify template mask
    │   │   │   ├── fa.mif.gz                          <-- DTI-fit, FA map
    │   │   │   ├── mask.mif.gz
    │   │   │   ├── odf_csf_normed_cyo.mif.gz          <-- fluid component ODF, intensity, normalised
    │   │   │   ├── odf_csf_normed_native.mif.gz       <-- subject-native fluid image
    │   │   │   ├── odf_o_normed_cyo.mif.gz            <-- Ao: older-appearing tissue component
    │   │   │   ├── odf_wm_gm_normed_native.mif.gz     <-- subject-native tissue image
    │   │   │   └── odf_y_normed_cyo.mif.gz            <-- Ay: younger-appearing tissue component, normalised
    │   │   ├── 34.0
...
    ├── metadata
    │   ├── rf_native                                   <-- subject-specific response functions
    │   │   ├── sub-CC00063AN06_ses-15102_36_csf.txt    <-- CSF response function for this subject (PMA: 36w)
    │   │   ├── sub-CC00063AN06_ses-15102_36_wm_gmi.txt
    │   │   ├── sub-CC00065XX08_ses-18600_41_csf.txt
    │   │   ├── sub-CC00065XX08_ses-18600_41_wm_gmi.txt
    │   │   ├── sub-CC00067XX10_ses-20200_40_csf.txt

...
    │   ├── rf_csf_all                                  <-- group-average response functions
    │   ├── rf_tissue_32.9
    │   ├── rf_tissue_44.1
    │   ├── sub_ses_ga_32.9                             <-- subject identitifers per age group
    │   ├── sub_ses_ga_34.0
    │   ├── sub_ses_ga_35.2
    │   ├── sub_ses_ga_35.7
    │   ├── sub_ses_ga_37.1
    │   ├── sub_ses_ga_38.1
    │   ├── sub_ses_ga_39.1
    │   ├── sub_ses_ga_40.1
    │   ├── sub_ses_ga_40.9
    │   ├── sub_ses_ga_42.0
    │   ├── sub_ses_ga_42.8
    │   └── sub_ses_ga_44.1
    └── rigid
        ├── mean
        │   ├── 32.9
        │   │   ├── adc.mif.gz
        │   │   ├── count.mif.gz
        │   │   ├── fa.mif.gz
        │   │   ├── mask.mif.gz
        │   │   ├── odf_csf_normed_cyo.mif.gz
        │   │   ├── odf_csf_normed_native.mif.gz
        │   │   ├── odf_o_normed_cyo.mif.gz
        │   │   ├── odf_wm_gm_normed_native.mif.gz
        │   │   └── odf_y_normed_cyo.mif.gz
        │   ├── 34.0
...
datacite.yml
Title Atlas: A framework for multi-component analysis of diffusion MRI data over the neonatal period
Authors Pietsch,Maximilian
Christiaens,Daan
Hutter,Jana
Cordero-Grande,Lucilio
Price,Anthony N
Hughes,Emer
Edwards,A David
Hajnal,Joseph V
Counsell,Serena J
Tournier,J-Donald
Description A neonatal brain atlas derived from advanced multi-shell high angular resolution diffusion imaging data acquired as part of the Developing Human Connectome Project. We decompose images from 113 babies scanned after birth (33 to 44 weeks postmenstrual age) into developmentally meaningful orientation-resolved components to characterise tissue properties of neonatal brain development.
License CC0 1.0 Universal (CC0 1.0) - Public Domain Dedication (https://creativecommons.org/publicdomain/zero/1.0/)
References pietsch2018framework [doi:10.1016/j.neuroimage.2018.10.060] (IsSupplementTo)
Funding ERC, FP7/20072013 no. 319456 dHCP project
Wellcome/EPSRC Centre for Medical Engineering at Kings College London, WT 203148/Z/16/Z
MRC, MR/K006355/1
MRC, MR/L011530/1
NIHR Clinical Research Facility (CRF) at Guy's and St Thomas',
National Institute for Health Research Biomedical Research Centre based at Guy's and St Thomas' NHS Foundation Trust and King’s College London
Keywords Neuroscience
Diffusion MRI
Brain development
White matter
Atlas
Resource Type Dataset