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The MNI Structural maxprob thr25 2mm brain atlas is a probabilistic macro-anatomical parcellation of the human brain in MNI space, dividing the volume into discrete cortical and subcortical regions based on manual expert delineation of structural landmarks in multiple subjects, then aggregated and converted to maximum probability labels at 2 mm isotropic resolution with a threshold of 25% voxel-wise agreement across individuals. It parcellates gray-matter structures such as frontal, parietal, temporal, and occipital gyri, cingulate regions, insula, and deep nuclei, providing anatomically defined regions of interest rather than functionally or cytoarchitectonically derived areas. The atlas was constructed by aligning individual high-resolution structural MRIs to the MNI template, hand-segmenting major anatomical structures, estimating voxel-wise probabilities of each label, and assigning to each voxel the region with the highest probability when at least 25% of the sampled brains agreed on that label, yielding a “maxprob thr25” parcellation that balances anatomical consistency and coverage. It is widely used in neuroimaging for region-based analyses such as extracting mean signal from structural or functional data, anatomical localization of activation clusters, ROI-based connectivity studies, and as a reference for automated labeling in packages like FSL, SPM, and other MNI-based pipelines. Atlas Website
Overview generated by GPT-4o (2026).
Click any region name to view its full visualization and description.
| ID | Acronym | Region |
|---|---|---|
| 1 | Caudate | caudate_bilateral |
| 2 | Cerebellum | cerebellum_bilateral |
| 3 | Frontal Lobe | frontal lobe_bilateral |
| 4 | Insula | insula_bilateral |
| 5 | Occipital Lobe | occipital lobe_bilateral |
| 6 | Parietal Lobe | parietal lobe_bilateral |
| 7 | Putamen | putamen_bilateral |
| 8 | Temporal Lobe | temporal lobe_bilateral |
| 9 | Thalamus | thalamus_bilateral |
Wali Sidiqyar*, Gaurav Rudravaram*, Elyssa M. McMaster, Trent M. Schwartz, Adam M. Saunders, Kurt G. Schilling, Bennett A. Landman "Introducing SPINS: A Shared Public Visualization Library of Neuroanatomical Structures." Medical Imaging with Deep Learning- short paper
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