Obtaining completely stable cellular neural network templates for ultrasound image segmentation

Abstract

Cellular neural networks (CNNs) have been successfully applied to image segmentation problem. Nevertheless, the main difficulty remains in the process of creating appropriate templates to solve a segmentation problem. In this paper we present machine learning approach to obtain completely stable CNN templates and compare the obtained results to unconstrained machine learning approach. Despite introduced constraints of templates stability the results are comparable to unobstructed ones.