Extending the work from the PD25 template (Xiao et al. 2015, 2017), new population-based multi-contrast templates for 126 Parkinson’s patients and 17 controls are presented here. Nine 3T MRI image contrasts are included: T1w (MPRAGE), T2w, T1-T2 fusion, R2*, T2w, PDw, fluid-attenuated inversion recovery (FLAIR), neuromelanin-sensitive imaging, and improved susceptibility-weighted imaging (CLEAR-SWI; following methods from Eckstein et al. 2021).

Methods from Xiao et al. 2015 were used to create a T1–T2* fusion MRI volume for each subject that visualizes both cortical and subcortical structures to drive groupwise registration to create the population-based multi-contrast unbiased templates PD126 (shown in figures above) and CTRL17. The finished template is in the same space as the MNI PD25 template, which is the ICBM152 space.

FYI: The subjects used to create these templates were processed differently than the subjects used in the PD25 template. Specifically, the subject data was registered in stx space using an in-house PPMI model (Marek et al. 2011), instead of the ICBM152 model (although both are in ICBM152 stx space). This difference and the different sample of PD patients and controls, changes the scale and shape of the PD126/CTRL17 template by a small amount in comparison to the PD25 template, and hence the PD25 atlas labels do not align exactly on the PD126/CTRL17 templates.

The neuromelanin-sensitive imaging contrast is available in 1×1×1 mm and 0.3×0.3×0.3 mm resolutions, and were created using data from 85 PD patients and 13 controls with neuromelanin data. All other templates are available in three different resolutions: 1×1×1 mm, 0.5×0.5×0.5 mm, and 0.3×0.3×0.3 mm using the full 126 PD patients (44 female; ages=40-87), and 17 healthy controls (13 female; ages=39-84).

The template files that are available include:

PD126

• MPRAGE T1: PD126-T1MPRAGE-template-{0.3mm,0.5mm,1mm}
• T2*w: PD126-T2star-template-{0.3mm,0.5mm,1mm}
• T1-T2* fusion: PD126-fusion-template-{0.3mm,0.5mm,1mm}
• R2*: PD126-R2star- template-{0.3mm,0.5mm,1mm}
• T2w: PD126-T2w- template-{0.3mm,0.5mm,1mm}
• PDw: PD126-PDw- template-{0.3mm,0.5mm,1mm}
• FLAIR: PD126-FLAIR- template-{0.3mm,0.5mm,1mm}
• CLEAR-SWI: PD126-CLEARSWI-template -{0.3mm,0.5mm,1mm}
• NM: PD126-nm- template-{0.3mm,1mm}

CTRL17

• MPRAGE T1: CTRL17-T1MPRAGE-template-{0.3mm,0.5mm,1mm}
• T2*w: CTRL17-T2star-template-{0.3mm,0.5mm,1mm}
• T1-T2* fusion: CTRL17-fusion-template-{0.3mm,0.5mm,1mm}
• R2*: CTRL17-R2star- template-{0.3mm,0.5mm,1mm}
• T2w: CTRL17-T2w- template-{0.3mm,0.5mm,1mm}
• PDw: CTRL17-PDw- template-{0.3mm,0.5mm,1mm}
• FLAIR: CTRL17-FLAIR- template-{0.3mm,0.5mm,1mm}
• CLEAR-SWI: CTRL17-CLEARSWI- template-{0.3mm,0.5mm,1mm}
• NM: CTRL17-nm- template -{0.3mm,1mm}

1. V. Madge, V. S. Fonov, Y. Xiao, L. Zou, C. Jackson, R. B. Postuma, A. Dagher, E. A. Fon, D. L. Collins. “A dataset of multi-contrast unbiased average MRI templates of a Parkinson’s disease population,” Data in Brief, vol. 48, pp. 1-9, 2023.

MNI-FTD Templates: Unbiased Average Templates of Frontotemporal Dementia Variants

Standard anatomical templates are widely used in human neuroimaging processing pipelines to facilitate group level analyses and comparisons across different subjects and populations. The MNI-ICBM152 template is the most commonly used standard template, representing an average of 152 healthy young adult brains. However, in patients with neurodegenerative diseases such as frontotemporal dementia (FTD), the high levels of atrophy lead to significant differences between the brain shape of the individuals and the MNI-ICBM152 template. Such differences might inevitably lead to registration errors or subtle biases in downstream analyses and results. Disease-specific templates are therefore desirable to reflect the anatomical characteristics of the populations of interest and to reduce potential registration errors when processing data from such populations.

Here, we present MNI-FTD136, MNI-bvFTD70, MNI-svFTD36, and MNI-pnfaFTD30, four unbiased average templates of 136 FTD patients, 70 behavioural variant (bv), 36 semantic variant (sv), and 30 progressive nonfluent aphasia (pnfa) variant FTD patients as well as a corresponding age matched average template of 133 healthy controls (MNI-CN133), along with probabilistic tissue maps for each template. The public availability of these templates will facilitate analyses of FTD cohorts and enable comparisons between different studies in a common standardized space appropriate to FTD populations. All templates are here.

CerebrA atlas

Accurate anatomical atlases are recognized as important tools in brain-imaging research. They are widely used to estimate disease-specific changes and therefore, are of great relevance in extracting regional information on volumetric variations in clinical cohorts in comparison to healthy populations. The use of high spatial resolution magnetic resonance imaging and the improvement in data preprocessing methods have enabled the study of structural volume changes on a wide range of disorders, particularly in neurodegenerative diseases where different brain morphometry analyses are being broadly used in an effort to improve diagnostic biomarkers. In the present dataset, we introduce the Cerebrum Atlas (CerebrA) along with the MNI-ICBM2009c average template. MNI-ICBM2009c is the most recent version of the MNI-ICBM152 brain average, providing a higher level of anatomical details. Cerebra is based on an accurate non-linear registration of cortical and subcortical labelling from Mindboggle 101 to the symmetric MNI-ICBM2009c atlas, followed by manual editing.

MINC2 MINC1 NIFTI

 

 

 

BigBrain co-registration

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

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Publications

1. 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,” accepted in Data in Brief, 2017.
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, S. Beriault, G. Bruce Pike, and D. Louis Collins, “Multicontrast multiecho FLASH MRI for targeting the subthalamic nucleus,” Magnetic Resonance Imaging, vol. 30, pp. 627-640, 2012.

If you are using the BigBrain atlas co-registration dataset, please refer to the following preprint:

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

If you are using the Big Brain data, please cite the following publication:

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

Copyright

Copyright (C) 2016,2017,2018 Yiming Xiao, McConnell Brain Imaging Centre,
Montreal Neurological Institute, McGill University.

License

PD25 atlases are distributed under CC BY-NC-SA 3.0 Licence

Dataset for BigBrain co-registration with PD25 and ICBM152 is under CC BY 4.0 Licence. Note that this exception to the existing BigBrain dataset does not alter the general term of the license for the use of BigBrain itself, which is still under CC BY-NC-SA 4.0 License.

Download

Version 20170213: Download archives containing brain atlases, brain masks, midbrain and subcortical segmentation and histological labels: MINC1, MINC2, NIFTI

Version 20160706: Download archives containing brain atlases, brain masks and midbrain segmentation: MINC1, MINC2, NIFTI

Co-registration of BigBrain with PD25 and ICBM152 atlases: Download archives containing registered Big Brain atlas, manual segmentations, and registration transformation (only available in MINC2 package): MINC2, NIFTI

We present an unbiased magnetic resonance imaging template brain volume for pediatric data from birth to 4.5y age range. These volumes were created using 317 scans from 108 children enrolled in the NIH-funded MRI study of normal brain development (Almli et al., 2007, Evans and Group 2006).

Tools for using these atlases can be found in the Software section.

Publications

The following publications should be referenced when using this atlas:

VS Fonov, AC Evans, RC McKinstry, CR Almli and DL Collins Unbiased nonlinear average age-appropriate brain templates from birth to adulthood NeuroImage, Volume 47, Supplement 1, July 2009, Page S102 Organization for Human Brain Mapping 2009 Annual Meeting, DOI: 10.1016/S1053-8119(09)70884-5

License

Copyright (C) 1993–2004 Vladimir S. Fonov, Louis Collins, McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University. Permission to use, copy, modify, and distribute this software and its documentation for any purpose and without fee is hereby granted, provided that the above copyright notice appear in all copies. The authors and McGill University make no representations about the suitability of this software for any purpose. It is provided “as is” without express or implied warranty. The authors are not responsible for any data loss, equipment damage, property loss, or injury to subjects or patients resulting from the use or misuse of this software package.

Viewing

To view the atlases online, click on the appropriate JIV2 link in the Download section below.

Online viewing requires Java browser support. The Java Internet Viewer (JIV2) used here is available for download and personal use under the GNU general public license (GPL).

When viewing, the stereotaxic coordinates (X,Y,Z) are displayed in the first row below the volumes. One can use the left most mouse button to click on any image, and the other cross-sectional images will be updated with the appropriate position. You can also hold the middle/rocker mouse button down while moving up or down, to pan through the image plane. Holding ‘Shift’ with the left or middle button will enable dragging and zooming. When looking at the images, remember that left is left and right is right!

Download

You can download templates constructed for different age ranges. For each age range you will get an average T1w, T2w, PDw maps normalized between 0 and 100. Also each age range includes a binary brain mask. NOTE that these templates are smaller then standard MNI-152 template, so if you use them to perform registration in stereotaxic space it will be different coordinate system. It is possible to transform results to MNI-152 space by applying following scaling: 1.21988 in x direction, 1.23510 in y direction and 1.28654 in z direction. Also, you can apply transformation defined in nihpd_asym_44–60_tal.xfm file.

• All templates for all age ranges in one archive: MINC1 388MB, MINC2 387MB, NIFTI 375MB,T1w JIV2

We present an unbiased standard magnetic resonance imaging template brain volume for pediatric data from the 4.5 to 18.5y age range. These volumes were created using data from 324 children enrolled in the NIH-funded MRI study of normal brain development (Almli et al., 2007, Evans and Group 2006). Tools for using these atlases can be found in the Software section.

Viewing

To view the atlases online, click on the appropriate JIV2 link in the Download section below.

Online viewing requires Java browser support. The Java Internet Viewer (JIV2) used here is available for download and personal use under the GNU general public license (GPL).

When viewing, the MNI stereotaxic coordinates (X,Y,Z) are displayed in the first row below the volumes. One can use the left most mouse button to click on any image, and the other cross-sectional images will be updated with the appropriate position. You can also hold the middle/rocker mouse button down while moving up or down, to pan through the image plane. Holding ‘Shift’ with the left or middle button will enable dragging and zooming. When looking at the images, remember that left is left and right is right!

Methods

The pediatric average atlases are comprised of:

Image pre-processing included non-uniform intensity correction (Sled, 1998) and intensity normalization to a range of 0–100. All T1w MRI data was then transformed into the Talairach-like MNI stereotaxic space using minctracc (Collins, Neelin et al. 1994). Brain masking was performed using BET (Smith, 2002). Age-based subgroups of subjects were created, and all scans within each group were then automatically re-registered to the stereotaxic space using the appropriate template. For each group, an iterative nonlinear co-registration algorithm (Grabner, Janke et al. 2006, Fonov, 2010), was applied to obtain the group averages. The T1-based transformation was then applied to the T2, PD and tissue classified volumes to generate average atlases for these data. Methodological details can be found in (Fonov, 2010).

Publications

The following publications should be referenced when using this atlas:

VS Fonov, AC Evans, K Botteron, CR Almli, RC McKinstry, DL Collins and BDCG, Unbiased average age-appropriate atlases for pediatric studies, NeuroImage, In Press, ISSN 1053–8119, DOI:10.1016/j.neuroimage.2010.07.033

VS Fonov, AC Evans, RC McKinstry, CR Almli and DL Collins Unbiased nonlinear average age-appropriate brain templates from birth to adulthood NeuroImage, Volume 47, Supplement 1, July 2009, Page S102 Organization for Human Brain Mapping 2009 Annual Meeting, DOI: 10.1016/S1053-8119(09)70884-5

License

Copyright (C) 1993–2004 Vladimir S. Fonov, Louis Collins, McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University. Permission to use, copy, modify, and distribute this software and its documentation for any purpose and without fee is hereby granted, provided that the above copyright notice appear in all copies. The authors and McGill University make no representations about the suitability of this software for any purpose. It is provided “as is” without express or implied warranty. The authors are not responsible for any data loss, equipment damage, property loss, or injury to subjects or patients resulting from the use or misuse of this software package.

Comparing different ages

To compare between different paediatric atlases, click here and choose the desired ages. Note that the adult template is also included for reference (18.5–43 y.o): ICBM 152 Nonlinear atlases version 2009.

Download

You can download templates constructed for different age ranges. For each age range you will get an average T1w, T2w, PDw maps normalized between 0 and 100 and tissue probability maps, with values between 0 and 1. Also each age range includes a binary brain mask.

Left-Right Symmetric templates

• All Left-Right Symmetric templates for all age ranges in one archive: MINC1 357MB, MINC2 356MB, NIFTI 338MB, or JIV2 (for online viewing)
• 4.5–18.5 y.o (the whole age range): MINC1 61MB, MINC2 61MB, NIFTI 57MB, or JIV2 (for online viewing)
• 4.5–8.5 y.o (prepuberty): MINC1 59MB,MINC2 59MB, NIFTI 56MB, or JIV2 (for online viewing)
• 7–11 y.o (pre- to early puberty): MINC1 59MB, MINC2 59MB, NIFTI 56MB, or JIV2 (for online viewing)
• 7.5–13.5 y.o (pre- to mid puberty): MINC1 60MB, MINC2 60MB, NIFTI 57MB, or JIV2 (for online viewing)
• 10–14 y.o (early to advanced puberty): MINC1 60MB, MINC2 60MB, NIFTI 57MB, or JIV2 (for online viewing)
• 13–18.5 y.o (post puberty): MINC1 60MB, MINC2 60MB, NIFTI 57MB, or JIV2 (for online viewing)

Asymmetric (natural) templates

• All Asymmetric (natural) templates for all age ranges in one archive: MINC1 357MB, MINC2 356MB, NIFTI 338MB, or JIV2 (for online viewing)
• 4.5–18.5 y.o (the whole age range): MINC1 60MB, MINC2 60MB, NIFTI 57MB, or JIV2 (for online viewing)
• 4.5–8.5 y.o (prepuberty): MINC1 59MB, MINC2 59MB, NIFTI 57MB, or JIV2 (for online viewing)
• 7–11 y.o (pre- to early puberty): MINC1 59MB, MINC2 59MB, NIFTI 57MB, or JIV2 (for online viewing)
• 7.5–13.5 y.o (pre- to mid puberty): MINC1 59MB, MINC2 59MB, NIFTI 57MB, or JIV2 (for online viewing)
• 10–14 y.o (early to advanced puberty): MINC1 59MB, MINC2 59MB, NIFTI 57MB, or JIV2 (for online viewing)
• 13–18.5 y.o (post puberty): MINC1 60MB, MINC2 60MB, NIFTI 57MB, or JIV2 (for online viewing)

Contact

For questions related to the MNI NIHPD atlases (rather than the website), contact Vladimir Fonov

Colin 27 Average Brain, Stereotaxic Registration Model, high-resolution version 2008

The anatomical phantom is derived from T1, T2, PD-weighted images formed from the average of 27, 11 and 12 scans respectively, of the same normal subject. These volumes are defined at a 0.5mm isotropic voxel grid in Talairach space, with dimensions 362*434*362 (XxYxZ) and start coordinates −90,−126,−72 (x,y,z). A discrete phantom was created by storing the label of the most important fraction class at each voxel location

Publications

1. Holmes CJ, Hoge R, Collins DL, Woods R, Toga AW, Evans AC. “Enhancement of MR images using registration for signal averaging.” J Comput Assist Tomogr. 1998 Mar-Apr;22(2):324–33. https://dx.doi.org/10.1097/00004728-199803000-00032
2. B Aubert-Broche, AC Evans, and DL Collins, “A new improved version of the realistic digital brain phantom,” NeuroImage, vol. 32, no. 1, pp. 138–45, 2006. https://www.ncbi.nlm.nih.gov/pubmed/16750398

License
Copyright (C) 1993–2009 Louis Collins, McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University. Permission to use, copy, modify, and distribute this software and its documentation for any purpose and without fee is hereby granted, provided that the above copyright notice appear in all copies. The authors and McGill University make no representations about the suitability of this software for any purpose. It is provided “as is” without express or implied warranty. The authors are not responsible for any data loss, equipment damage, property loss, or injury to subjects or patients resulting from the use or misuse of this software package.

Download
Download archives containing average t1w, t2w and pdw scan, and discrete tissue classification: 1: Cerebro-spinal fluid, 2: Gray Matter, 3: White Matter, 4: Fat, 5: Muscles, 6: Skin and Muscles, 7: Skull, 9: Fat 2, 10: Dura, 11: Marrow, 12: Vessels
MINC1 222MB MINC2 223MB NIFTI 291MB

Fuzzy segmentation

Stereotaxic Registration Model, original 1998 version

This is a stereotaxic average of 27 T1-weighted MRI scans of the same individual. In 1998, a new atlas with much higher definition than MNI305s was created at the MNI. One individual (CJH) was scanned 27 times and the images linearly registered to create an average with high SNR and structure definition (Holmes et al., 1998). This average was linearly registered to the average 305. Ironically, this dataset was not originally intended for use as a stereotaxic template but as the sub- strate for an ROI parcellation scheme to be used with ANIMAL non-linear spatial normalization (Collins et al., 1995), i.e. it was intended for the purpose of segmentation, NOT stereotaxy. As a single brain atlas, it did not capture anatomical variability and was, to some degree, a reversion to the Talairach approach.

However, the high definition proved too attractive to the community and, after non-linear mapping to fit the MNI305 space, it has been adopted by many groups as a stereotaxic template (e.g., AFNI, Cox,; Brainstorm, Tadel et al., 2011; SPM, Litvak et al., 2011; Fieldtrip, Oostenveld et al., 2011).

Methods

This average dataset was created in a two step process. First, each of the 27 T1-weighted scans were registered to stereotaxic space using the mritotal procedure and resampled onto a 1mm grid in stereotaxic space. All 27 scans were averaged together to create an initial average. This average volume was used as a target for the second phase of registration where each original T1-weighted MRI was re-registered in stereotaxic space. This procedure has the advantage of removing the small variance in intra-subject mapping in stereotaxic space associated with the use of a multi-subject average.

Holmes CJ, Hoge R, Collins L, Woods R, Toga AW, Evans AC. “Enhancement of MR images using registration for signal averaging.” J Comput Assist Tomogr. 1998 Mar-Apr;22(2):324–33. https://dx.doi.org/10.1097/00004728-199803000-00032

 License
Copyright (C) 1993–2009 Louis Collins, McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University. Permission to use, copy, modify, and distribute this software and its documentation for any purpose and without fee is hereby granted, provided that the above copyright notice appear in all copies. The authors and McGill University make no representations about the suitability of this software for any purpose. It is provided “as is” without express or implied warranty. The authors are not responsible for any data loss, equipment damage, property loss, or injury to subjects or patients resulting from the use or misuse of this software package.

Download

Download archives containing average t1w scan, brain mask and head mask: MINC1 13MB MINC2 13MB NIFTI 24MB