CONP Portal | Dataset

Keywords: MRI BigBrain Atlas MNI PD25 human brain ICBM152
Accurate registration of the BigBrain dataset with the MNI PD25 and ICBM152 atlases
Creators: Yiming Xiao, Jonathan C. Lau, Taylor Anderson, Jordan DeKraker, D. Louis Collins, Terry M. Peters, Ali R. Khan
Principal Investigator: Ali R. Khan
Contact: Ali R. Khan, Khan Computational Imaging Lab, Robarts Research Institute, University of Western Ontario alik@robarts.ca
Licenses: CC BY-4.0
Version: 1.0.0
Modalities: Histology
Formats: MINC NIfTI
Size: 11.0 GB
No of Files: 75
No of Subjects: 1
Browse on GitHub: https://github.com/conpdatasets/BigBrainMRICoreg
Project Landing Page: https://github.com/khanlab-datasets/BigBrainMRICoreg
Metadata file: DATS.json
Other Dates: Start Date: 2019-03-19 00:00:00
Description:
Co-registration of the BigBrain atlas with the MNI PD25 and ICBM152 atlases

Dataset README information

README.md

This dataset includes co-registration of the BigBrain dataset to the MNI PD25 atlas and the ICBM152 2009b atlases.
The data include deformed BigBrain atlases and manual subcortical segmentations in MINC2 and NIFTI-1 formats, as well as relevant spatial transformation in MINC transformation format.
The segmented subcortical structures include: red nucleus, subthalamic nucleus, substantia nigra, caudate, putamen, globus pallidus externa, globus pallidus interna, thalamus, hippocampus

Note that the described improved co-registration was performed upon the BigBrain data in ICBM space from the BigBrain 2015release.

Within this dataset, the down-sampled versions of BigBrain atlases are distributed under the CC BY4.0 License upon the consent from the original data owners, the Montreal Neurological Institute
(Montreal, Canada) and the Forschungszentrum Jülich (Jülich, Germany). However, this exception to the existing BigBrain dataset does not alter the general term of that license for use of the
BigBrain itself, which is still under the CC BY-NC-SA 4.0 License.

The included files are as follows:

  1. Deformed BigBrain atlases:
    BigBrain in PD25 space: BigBrain-to-PD25-nonlin-{300um, 0.5mm, 1mm}
    BigBrain in ICBM152 symmetric atlas: BigBrain-to-ICBM2009sym-nonlin-{300um, 0.5mm, 1mm}
    BigBrain in ICBM152 asymmetric atlas: BigBrain-to-ICBM2009asym-nonlin-{300um, 0.5mm, 1mm}
    Synthetic T2w PD25 atlas: PD25-SynT2-template-{300um, 0.5mm, 1mm}
    T1-T2* fusion PD25 atlas: PD25-enhanceFusion-template-{300um, 0.5mm, 1mm}

  2. Manual subcortical segmentations:
    BigBrain coregistered to ICBM in the BigBrain2015 release: BigBrain-segmentation-0.3mm
    MNI PD25: PD25-segmentation-0.5mm
    ICBM152 2009b symmetric: ICBM2009b_sym-segmentation-0.5mm
    ICMB152 2009b asymmetric: ICBM2009b_asym-segmentation-0.5mm

  3. Related transformations:
    BiBrain-to-PD25: BigBrain-to-PD25-nonlin.xfm
    BigBrain-to-ICBM2009asym: BigBrain-to-ICBM2009asym-nonlin.xfm
    BigBrain-to-ICBM2009sym: BigBrain-to-ICBM2009sym-nonlin.xfm
    PD25-to-ICBM2009asym: PD25-to-ICBM2009asym-nonlin.xfm
    PD25-to-ICBM2009sym: PD25-to-ICBM2009sym-nonlin.xfm

  4. List of subcortical labels: subcortical-labels.csv

References:

For the methods used, please cite the following articles:

  1. Y. Xiao, J.C. Lau, T. Anderson,J. DeKraker, D. Louis Collins, T.M. Peters, and A.R. Khan, “Bridging micro and macro:
    accurate registration of the BigBrain dataset with the MNI PD25 and ICBM152 atlases,” bioRxiv, 561118, Cold Spring Harbor Laboratory,
    doi: https://doi.org/10.1101/561118.

  2. Y. Xiao, V. Fonov, S. Beriault, F.A. Subaie, M.M. Chakravarty, A.F. Sadikot,
    G. Bruce Pike, and D. Louis Collins, “Multi-contrast unbiased MRI atlas of a
    Parkinson's disease population,” International Journal of Computer-Assisted
    Radiology and Surgery, vol. 10(3), pp. 329-341, 2015.

3.Y. Xiao, V. Fonov, S. Beriault, F.A. Subaie, M.M. Chakravarty, A.F. Sadikot, G. Bruce Pike, and D. Louis Collins,
“A dataset of multi-contrast population-averaged brain MRI atlases of a Parkinson’s disease cohort,”Data in Brief, 2017.

When using the downsamled BigBrain atlases, please cite the following article:

  1. Amunts, K. et al.: “BigBrain: An Ultrahigh-Resolution 3D Human Brain Model”, Science (2013) 340 no. 6139 1472-1475, June 2013

Download Using DataLad

CircleCI status

The following instructions require a basic understanding of UNIX/LINUX command lines. A subset of open datasets on the Portal are also available through a browser-based download button. The instructions below regard dataset download with the use of DataLad. To install DataLad on your system, please refer to the install section of the DataLad Handbook .

Note: For maximum compatibility with conp-dataset, the CONP recommends versions 3.12+ of Python, 10.20241202+ of git-annex, and 1.1.4+ of datalad.

1) Initiate the CONP dataset

Run the following command in the directory where you want the CONP dataset (conp-dataset) to be installed:

2) Install the Khanlab/BigBrainMRICoreg dataset

To install the Khanlab/BigBrainMRICoreg dataset, run the following commands to move into the "projects" subdirectory under the "conp-dataset" directory (created in the previous step) and run datalad install:

3) Download data from the Khanlab/BigBrainMRICoreg dataset

Now that the dataset has been installed, go into the Khanlab/BigBrainMRICoreg dataset directory.

The files visible after installing the dataset but before downloading (in the next step) are symbolic links and need to be downloaded manually using the datalad get command:

If you run datalad get * command, all the files available in the dataset directory will be downloaded.


For more information on how DataLad works, please visit the DataLad Handbook documentation.