A review of applications of automated ventricular parcellation from magnetic resonance imaging of the brain
Ventricular parcellation or segmentation is the systematic assignment of pixels (or voxels), from an image of the brain, to the ventricular compartment. As opposed to manual methods, automated techniques seek to streamline segmentation for better, objective delineation of the ventricles. The refinement of these methods, powered by advances in computer vision, has provided significant biological insight into the pathogenesis of many neurological diseases affecting both adults and children. In this article, we present a review of applications of automated ventricular segmentation from magnetic resonance imaging (MRI) and offer a brief primer on brain segmentation methods to non-technical readers.
Authors
- Leopold Arko (ORCID: https://orcid.org/0000-0003-1052-5671)
- Noam Harel (ORCID: https://orcid.org/0000-0002-6034-3801)
- Carolina Sandoval-Garcia (ORCID: https://orcid.org/0000-0003-1418-3568)
- Robert A. McGovern (ORCID: https://orcid.org/0000-0003-0752-1899)
- Birra Taha (ORCID: https://orcid.org/0000-0001-5817-5258)
- Daniel Guillaume
- Alexandra Benson
Institutions
- University of Minnesota (US)
- Normandale Community College (US)
- Resonance Research (United States) (US)
Publication Details
- Journal
- Frontiers in Neurology
- Published
- 2026-04-01
- DOI
- https://doi.org/10.3389/fneur.2025.1639381
- Primary Topic
- Medical Image Segmentation Techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.00