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We provide a set of tools packaged as purple-mri for segmentation, parcellation and registration of ultra high-resolution (< 300 microns) postmortem human brain hemisphere at 7 tesla t2w MRI at native subject-space resolution. This pipeline leverages advances in both deep learning and classical surface-based modeling techniques to produce parcellations in any atlas used in neuroimaging. The developed method allows us to perform vertex-wise analysis in the template space and thereby link morphometry measures with pathology measurements derived from histology.
Perform bias correction and image normalization/standardization. We use N4BiasFieldCorrection as part of the CLI tool ANTs and c3d. We highly recommend using the option of an input mask in N4BiasFieldCorrection which can be obtained via corase threhsolding. Here is a sample script.
Currently, we have two Docker images. The first image provides the segmentation and the second employs Nighres/CRUISE for post-hoc topology correction. Please follow the [link](https://github.com/Pulkit-Khandelwal/upenn-picsl-brain-ex-vivo/blob/main/exvivo-segm-demo-docker.md for detailed instructions on how to use Docker to get the segmentations. Some key commands are emphasized here:
