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'''WORK IN PROGRESS''' |
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| * [[attachment:load_gca.m]] | |
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| * [[attachment:load_gca.m]] |
The .gca file is composed of three volumes, which can be extracted like this: {{{ mri_convert atlas.gca -nth 0 means.mgz mri_convert atlas.gca -nth 1 labels.mgz mri_convert atlas.gca -nth 2 priors.mgz }}} where: * labels --> indices of the most likely label at each voxel * priors --> the probability that that label occurs at that voxel * means --> the mean intensity of the most likely label |
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The GCA Subcortical Segmentation Atlas Volume Format
The .gca (Gaussian Classifier Atlas) file format encodes voxel label information based on probabilistic information estimated from a training set. The GCA format is proprietary, defined by the NMR Center (at Massachusetts General Hospital). Below is an informal specification of the format, extracted from the code snippets below:
The .gca file is composed of three volumes, which can be extracted like this:
mri_convert atlas.gca -nth 0 means.mgz mri_convert atlas.gca -nth 1 labels.mgz mri_convert atlas.gca -nth 2 priors.mgz
where:
labels --> indices of the most likely label at each voxel
priors --> the probability that that label occurs at that voxel
means --> the mean intensity of the most likely label
References
Whole Brain Segmentation: Automated Labeling of Neuroanatomical Structures in the Human Brain, Fischl, B., D.H. Salat, E. Busa, M. Albert, M. Dieterich, C. Haselgrove, A. van der Kouwe, R. Killiany, D. Kennedy, S. Klaveness, A. Montillo, N. Makris, B. Rosen, and A.M. Dale, (2002). Neuron, 33:341-355.
Sequence-Independent Segmentation of Magnetic Resonance Images, Fischl, B., Salat, D.H., van der Kouwe, A.J.W., Makris, N., Ségonne, F., and Dale, A.M. (2004) NeuroImage 23:S69-S84.
Atlas Renormalization for Improved Brain MR Image Segmentation Across Scanner Platforms, Han, X. and B. Fischl, (2007). IEEE Transactions on Medical Imaging, 26(4):479-486.