Group theoretic particle swarm optimization for multi-level threshold lung cancer image segmentation.

ABSTRACT:

Background

Image segmentation is an important step during the processing of medical images. For example, for the computer aid diagnostic systems for lung cancer image analysis, the segmented regions of tumors would help doctors in early diagnosis to determine timely and appropriate treatment possibilities and thereby improve the survival rate of the patients. However, general clinical routines of manual segmentation for large number of medical images are very difficult and time consuming, which is the challenge we aim to tackle using our proposed method.

Methods

A novel image segmentation method with evolutionary learning technique named Group Theoretic Particle Swarm Optimization is proposed. It can tackle multi-level thresholding optimization problem during the segmentatio

SUBMITTER: Lan K 

PROVIDER: S-EPMC10006099 | biostudies-literature | 2023 Mar

REPOSITORIES: biostudies-literature