Advanced Texture Analysis Techniques for Building Textural Models, with Applications in the Study of the Pathology Evolution Stages, based on Ultrasound Images

Abstract

This chapter describes specific, texture-based methods for the detection, characterization and recognition of some severe affections and of their evolution phases, using only information from ultrasound images. We perform the recognition of the considered affections in supervised manner, and we also discover the disease evolution phases in unsupervised manner. In both cases, the imagistic textural model is defined, consisting of: the relevant features for the characterization of the disease, respectively of its evolution phase; the specific values of the relevant textural features: arithmetic mean, standard deviation, probability distribution. Advanced texture analysis techniques, consisting of textural microstructure co-occurrence matrices based on Laws' features, are involved in this process. At the end, the imagistic textural model is validated through powerful, supervised classifiers, the resulting accuracy being around 90%.