Accurate nonlinear mapping between MNI volumetric and FreeSurfer surface coordinate systems

Wu, Jianxiao; Li, Jingwei; Yeo, B. T. Thomas; Greve, Douglas; Fischl, Bruce; Ngo, Gia H.; He, Tong; Eickhoff, Simon

doi:10.1002/hbm.24213

Journal Article

FZJ-2018-03105

Accurate nonlinear mapping between MNI volumetric and FreeSurfer surface coordinate systems

Wu, J. ; Ngo, G. H. ; Greve, D. ; Li, J. ; He, T. ; Fischl, B. ; Eickhoff, S.FZJ* ; Yeo, B. T. T. (Corresponding author)

2018
Wiley-Liss New York, NY

Human brain mapping 39(9), 3793-3808 (2018) [10.1002/hbm.24213]

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Please use a persistent id in citations: http://hdl.handle.net/2128/21656 doi:10.1002/hbm.24213

Abstract: The results of most neuroimaging studies are reported in volumetric (e.g., MNI152) or surface (e.g., fsaverage) coordinate systems. Accurate mappings between volumetric and surface coordinate systems can facilitate many applications, such as projecting fMRI group analyses from MNI152/Colin27 to fsaverage for visualization or projecting resting-state fMRI parcellations from fsaverage to MNI152/Colin27 for volumetric analysis of new data. However, there has been surprisingly little research on this topic. Here, we evaluated three approaches for mapping data between MNI152/Colin27 and fsaverage coordinate systems by simulating the above applications: projection of group-average data from MNI152/Colin27 to fsaverage and projection of fsaverage parcellations to MNI152/Colin27. Two of the approaches are currently widely used. A third approach (registration fusion) was previously proposed, but not widely adopted. Two implementations of the registration fusion (RF) approach were considered, with one implementation utilizing the Advanced Normalization Tools (ANTs). We found that RF-ANTs performed the best for mapping between fsaverage and MNI152/Colin27, even for new subjects registered to MNI152/Colin27 using a different software tool (FSL FNIRT). This suggests that RF-ANTs would be useful even for researchers not using ANTs. Finally, it is worth emphasizing that the most optimal approach for mapping data to a coordinate system (e.g., fsaverage) is to register individual subjects directly to the coordinate system, rather than via another coordinate system. Only in scenarios where the optimal approach is not possible (e.g., mapping previously published results from MNI152 to fsaverage), should the approaches evaluated in this manuscript be considered. In these scenarios, we recommend RF-ANTs (https://github.com/ThomasYeoLab/CBIG/tree/master/stable_projects/registration/Wu2017_RegistrationFusion).

Classification:

ddc:610

Note: Singapore MOE Tier 2, Grant/Award Number: MOE2014‐T2‐2‐016; NUS Strategic Research, Grant/Award Number: DPRT/944/09/14; NUS SOM Aspiration Fund, Grant/Award Number: R185000271720; Singapore NMRC, Grant/Award Number: CBRG/0088/2015; NUS YIA; Singapore National Research Foundation (NRF) Fellowship (Class of 2017); Center for Functional Neuroimaging Technologies, Grant/Award Number: P41EB015896; Athinoula A. Martinos Center for Biomedical Imaging at the Massachusetts General Hospital, Grant/Award Numbers: 1S10RR023401, 1S10RR019307, 1S10RR023043; National Institute of Mental Health, Grant/Award Number: R01‐MH074457; Helmholtz Portfolio Theme “Supercomputing and Modeling for the Human Brain”; European Union's Horizon 2020 Research and Innovation Programme, Grant/Award Number: 7202070 (HBP SGA1); National Institute for Biomedical Imaging and Bioengineering, Grant/Award Numbers: P41EB015896, 1R01EB023281, R01EB006758, R21EB018907, R01EB019956; National Institute on Aging, Grant/Award Numbers: 5R01AG008122, R01AG016495; National Institute of Diabetes and Digestive and Kidney Diseases, Grant/Award Number: 1‐R21‐DK‐108277‐01; National Institute for Neurological Disorders and Stroke, Grant/Award Numbers: R01NS0525851, R21NS072652, R01NS070963, R01NS083534, 5U01NS086625; NIH Blueprint for Neuroscience Research, Grant/Award Number: 5U01‐MH093765

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