Artificial inteligence methods in diagnostics from medical images

The project is concerned with development of computer assistant diagnostic methods for medical ultrasound imaging, based on image processing methods, texture analysis, and pattern matching theory. We shall focus on the diagnostic of thyroid gland (such as the autoimmune lymphocytic disease), liver, and other accessible organs. We shall use texture analysis of the sonograms with systematic construction of the descriptors. We will also develop a method of elastographic analysis from a video-sequence of ultrasound images taken in the course of the deformation caused by the pressure from the sensing probe. This algorithm will use elastic image sequence registration method with a developed high-dimensionality mutual-information based similarity criterion, specially developed for this application. The method will distinguish between tissue types (e.g. tumor versus healthy tissue) according to their stiffness. Implemented algorithms will be tested on real clinical data.