Processing, analysis, recognition, and automatic understanding of medical images

摘要

Paper presents some new ideas introducing automatic understanding of the medical images semantic content. The idea under consideration can be found as next step on the way starting from capturing of the images in digital form as two-dimensional data structures, next going throw images processing as a tool for enhancement of the images visibility and readability, applying images analysis algorithms for extracting selected features of the images (or parts of images e.g. objects), and ending on the algorithms devoted to images classification and recognition. In the paper we try to explain, why all procedures mentioned above can not give us full satisfaction in many important medical problems, when we do need understand image semantic sense, not only describe the image in terms of selected features and/or classes. The general idea of automatic images understanding is presented as well as some remarks about the successful applications of such ides for increasing potential possibilities and performance of computer vision systems dedicated to advanced medical images analysis. This is achieved by means of applying linguistic description of the picture merit content. After this we try use new AI methods to undertake tasks of the automatic understanding of images semantics in intelligent medical information systems. A successful obtaining of the crucial semantic content of the medical image may contribute considerably to the creation of new intelligent multimedia cognitive medical systems. Thanks to the new idea of cognitive resonance between stream of the data extracted form the image using linguistic methods and expectations taken from the representation of the medical knowledge, it is possible to understand the merit content of the image even if the form of the image is very different from any known pattern.