Intelligent System for Classifying of Acoustic Endoscopic Images of the Pancreas Based the Analysis of Walsh Spectra of Local Windows

The purpose of the work is to develop and study methods and algorithms for intelligent classification systems for digital medical images. A method for automatic classification of medical images was developed using neural networks and transparency masks obtained by preliminary image segmentation. This allows you to generate descriptors only for those pixels that are selected by the transparency mask. Also algorithmic and software for classifying medical images has been developed. Experimental testing was carried out on ultrasound images of the pancreas. Differential diagnostics was carried out on control samples. The classes "oncology" and "pancreatitis" were divided. The diagnostic sensitivity by class turned out to be at least 0.8, while the diagnostic specificity is at least 0.85.