Fast predictive simple geodesic regression.

ABSTRACT: Deformable image registration and regression are important tasks in medical image analysis. However, they are computationally expensive, especially when analyzing large-scale datasets that contain thousands of images. Hence, cluster computing is typically used, making the approaches dependent on such computational infrastructure. Even larger computational resources are required as study sizes increase. This limits the use of deformable image registration and regression for clinical applications and as component algorithms for other image analysis approaches. We therefore propose using a fast predictive approach to perform image registrations. In particular, we employ these fast registration predictions to approximate a simplified geodesic regression model to capture longitudinal brain chan

SUBMITTER: Ding Z 

PROVIDER: S-EPMC6661182 | biostudies-literature | 2019 Aug

REPOSITORIES: biostudies-literature