Testing a convolutional neural network-based hippocampal segmentation method in a stroke population.

ABSTRACT: As stroke mortality rates decrease, there has been a surge of effort to study poststroke dementia (PSD) to improve long-term quality of life for stroke survivors. Hippocampal volume may be an important neuroimaging biomarker in poststroke dementia, as it has been associated with many other forms of dementia. However, studying hippocampal volume using MRI requires hippocampal segmentation. Advances in automated segmentation methods have allowed for studying the hippocampus on a large scale, which is important for robust results in the heterogeneous stroke population. However, most of these automated methods use a single atlas-based approach and may fail in the presence of severe structural abnormalities common in stroke. Hippodeep, a new convolutional neural network-based hippocampal segmen

SUBMITTER: Zavaliangos-Petropulu A 

PROVIDER: S-EPMC8675423 | biostudies-literature | 2022 Jan

REPOSITORIES: biostudies-literature