Fast three-dimensional image generation for healthy brain aging using diffeomorphic registration.
Ontology highlight
ABSTRACT: Predicting brain aging can help in the early detection and prognosis of neurodegenerative diseases. Longitudinal cohorts of healthy subjects scanned through magnetic resonance imaging (MRI) have been essential to understand the structural brain changes due to aging. However, these cohorts suffer from missing data due to logistic issues in the recruitment of subjects. This paper proposes a methodology for filling up missing data in longitudinal cohorts with anatomically plausible images that capture the subject-specific aging process. The proposed methodology is developed within the framework of diffeomorphic registration. First, two novel modules are introduced within Synthmorph, a fast, state-of-the-art deep learning-based diffeomorphic registration method, to simulate the aging process b
SUBMITTER: Fu J
PROVIDER: S-EPMC9921328 | biostudies-literature | 2023 Mar
REPOSITORIES: biostudies-literature
ACCESS DATA