A Transfer Learning Approach on the Optimization of Edge Detectors for Medical Images Using Particle Swarm Optimization.

ABSTRACT: Edge detection is a fundamental image analysis task, as it provides insight on the content of an image. There are weaknesses in some of the edge detectors developed until now, such as disconnected edges, the impossibility to detect branching edges, or the need for a ground truth that is not always accessible. Therefore, a specialized detector that is optimized for the image particularities can help improve edge detection performance. In this paper, we apply transfer learning to optimize cellular automata (CA) rules for edge detection using particle swarm optimization (PSO). Cellular automata provide fast computation, while rule optimization provides adaptability to the properties of the target images. We use transfer learning from synthetic to medical images because expert-annotated medica

SUBMITTER: Dumitru D 

PROVIDER: S-EPMC8066857 | biostudies-literature | 2021 Mar

REPOSITORIES: biostudies-literature