Радиологические изображения в создании гибридных интеллектуальных систем

Abstract

So far, the concept of image row or tuples in the development of intelligent systems has been discussed in relation to the role of phenotypic (external) manifestations of diseases in diagnostics. This study introduces the idea of neuroimaging tuples as a tool to make a prognosis of the course of chronic cerebral ischemia. The phenomenon of leukoaraiosis is analyzed as a radiological feature of chronic brain ischemia and a predictor of stroke. Image tuples are formed from the results of computed tomography, computed tomography angiography, magnetic resonance imaging, of 85 patients with chronic cerebral ischemia. Native computed tomography images were processed with adaptive filtering methods. Computed tomography angiography results were processed through a vesselness filter that allows development of 3D reconstructions of vasculature in leukoaraiosis areas. The problem of fuzzy images, the principles of comparative analysis of images and the possibility of using confidence factors in the image tuples are discussed in the article. A scheme of a hybrid intelligent system that combines traditional logic-linguistic rules and images based on primary information and reconstruction of the original DICOM images in the knowledge base was developed. The sphere of the application is stroke risk prediction using an intelligent system.