Article ; Online: An End-To-End Pipeline for Fully Automatic Morphological Quantification of Mouse Brain Structures From MRI Imagery.
Frontiers in bioinformatics
2022 Volume 2, Page(s) 865443
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 ... ...
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 |
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Language | English |
Publishing date | 2022-06-08 |
Publishing country | Switzerland |
Document type | Journal Article |
ISSN | 2673-7647 |
ISSN (online) | 2673-7647 |
DOI | 10.3389/fbinf.2022.865443 |
Database | MEDical Literature Analysis and Retrieval System OnLINE |
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