A new solution model for cardiac medical image segmentation.

ABSTRACT:

Background

Calculation methods have a critical role in the precise sorting of medical images. Particle swarm optimization (PSO) is a widely used approach in the clinical centers and for other medical applications as it can disentangle optimization errors in attached spaces. In this work, a new model for image segmentation is proposed through an improved optimization algorithm.

Methods

A novel multi-objective algorithm was configured, named "multi-objective mathematical programming" (MOMP), based on the normalized normal constraint method (NNCM). In this model, the proposed algorithm was applied to evaluate the robustness of the suggested model through including the synthetic images of objects with various concavities and Gaussian noise. This model segments the individuals' h

SUBMITTER: Shang H 

PROVIDER: S-EPMC7797822 | biostudies-literature | 2020 Dec

REPOSITORIES: biostudies-literature