Genetic algorithms for thyroid gland ultrasound image feature reduction

Abstract

The problem of automatic classification of ultrasound images is addressed. For texture analysis of ultrasound images quantifiable indexes, called features, are used. Classification was performed using Gaussian mixture model based on Bayes classifier. The common problem of texture analysis is a feature selection for classification tasks. In this work we use genetic algorithms for a feature subset selection. Total number of 387 features was used, consisting of spatial and co-occurance statistical texture features (proposed by Muzzolini and Haralick). The classification infers between healthy thyroid gland and thyroid gland with chronic inflammation. © Springer-Verlag Berlin Heidelberg 2005.