T1_T2_brainstem_seg_Matlab_code

Published: 16 March 2023| Version 1 | DOI: 10.17632/8pfjgrwtsr.1
Contributor:
Susanne Mueller

Description

T1_T2_brainstem segmentation Matlab routines The Matlab routines allow to segment internal brainstem structures from T1 and T2 weighted images. The routines are based on the method described in Hum Brain Mapp. 2020 Jun 1;41(8):2173-2186. doi: 10.1002/hbm.24938. In short, the intensities of the T1 and T2 images are re-scaled and a T1/T2 ratio image (RATIO) calculated. The brainstem is isolated and k-means clustering used to identify five intensity clusters. Nonlinear diffeomorphic mapping as implemented in SPMs DARTEL can be used to warp the five intensity clusters in subject space into a common space to project specific generate probabilistic group averages/priors. Alternatively, it is possible to use the priors provided in this directory. The priors are used to inform the final probabilistic segmentations at the single subject level. The five clusters correspond to five brainstem tissue types (2 gray matter, 2 mixed gray/white,1 csf/tissue partial volume). Please see Word document for detailed step-by-step instructions. Contact of author Susanne Mueller M.D. Center for Imaging of Neurodegenerative Diseases VAMC San Francisco 4150 Clement Street San Francisco, CA, 94121 USA e-mail: susanne.mueller@ucsf.edu You need to have Matlab with the Image Processing, Statistics, Curve Fitting, and Optimization toolboxes and spm12 (https://www.fil.ion.ucl.ac.uk/spm/) Make sure you have the T1_T2_brainstem_seg folder in you Matlab search path. The Matlab routines are not for commercial use. Disclaimer: Use of the Matlab routines at your own risk.

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Categories

Image Segmentation, Brainstem, Magnetic Resonance Imaging of Brain, T2 Contrast, T1 Contrast

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