Cognitive informatics in image semantics description, identification and automatic pattern understanding

In the paper a new way of pattern semantic interpretation directed at automatic semantic classification and image content understanding will be described. Such an understanding will be based on the linguistic theories of pattern classification and is aimed at facilitation of content analysis for some classes of medical patterns. The approach presented in this paper will show the great possibilities of automatic disease interpretation in some analyzed data. The interpretation will be based on cognitive processes, which imitate the psychological processes of understanding the registered patterns as they take place in the brain of a human being. Cognitive analysis will be based on languages of shape description and picture grammars which allow the creation of syntactic descriptions of selected anatomic organs together with a definition of the semantic meaning of the changes in their shapes. Such descriptions will further allow creating a semantically-oriented representation of visual data describing pattern features which are useful in medical decisions and computer-aided diagnostic systems. This publication presents the cognitive systems of medical data image analysis. Systems that conduct cognitive analyses are designed so that semantic analyses can be used to interpret data and reconstruct medical images. These systems are built for medical types of data analysis systems. An analysis in classical CIAIS (Cognitive Image Analysis Information Systems) will be used to illustrate and present the method of learning new solutions which the systems have no knowledge of. The proposed solution presents the method of building a new class of cognitive systems names E-CIAIS (Extended Cognitive Image Analysis Information Systems).

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