Active partition based medical image understanding with self-organised competitive spatch eduction
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Medical Image Understanding is a recently defined semantic oriented image recognition task. Its specific requirements, highlighting complex characteristics of recognised objects as well as indispensable use of human-level expert knowledge almost every step of data processing sets new requirements for implemented algorithms. This paper focuses on linguistic image description method, designed to segment low level, semantically coherent image regions and mine adjacency relations among them. Example method results on medical images are presented to specify some methods properties.
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