An End-To-End Pipeline for Fully Automatic Morphological Quantification of Mouse Brain Structures From MRI Imagery.

ABSTRACT: Segmentation of mouse brain magnetic resonance images (MRI) based on anatomical and/or functional features is an important step towards morphogenetic brain structure characterization of murine models in neurobiological studies. State-of-the-art image segmentation methods register image volumes to standard presegmented templates or well-characterized highly detailed image atlases. Performance of these methods depends critically on the quality of skull-stripping, which is the digital removal of tissue signal exterior to the brain. This is, however, tedious to do manually and challenging to automate. Registration-based segmentation, in addition, performs poorly on small structures, low resolution images, weak signals, or faint boundaries, intrinsic to in vivo MRI scans. To address thes

SUBMITTER: Alam S 

PROVIDER: S-EPMC9580949 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature