Region-based U-nets for fast, accurate, and scalable deep brain segmentation: Application to Parkinson Plus Syndromes.

ABSTRACT: The early diagnosis of age-related neurodegenerative diseases, which often progress to dementia, poses significant clinical challenges due to subtle and overlapping symptoms of these diseases at early stage. Automated MRI segmentation is important for early detection, as it offers consistent measurements and the ability to detect subtle structural changes in the brain. Manual segmentation is impractical for large datasets or clinical use. Deep learning approaches provide fast processing, however, they often encounter graphics processing unit (GPU) memory constraints when handling large datasets. Here we introduce a deep learning-based approach using region-based U-nets specifically designed to segment 12 deep-brain structures relevant to Parkinson Plus Syndromes. By dividing the brain imag

SUBMITTER: Li M 

PROVIDER: S-EPMC12269573 | biostudies-literature | 2025 Jun

REPOSITORIES: biostudies-literature