Data Aggregation Techniques in Heart Vessel Modelling and Recognition of Pathological Changes

One of the more important fields in which data aggregation methods could be applied is the analysis of medical images showing the complicated morphology of examined structures or organs. Such techniques support a comprehensive description of the analysed image and formulating the appropriate diagnosis by identifying the most important parameters of given structures, and then analysing their meaning by aggregating various information. In this paper is presented a proposal for the semantic analysis of the heart's coronary vessels for diagnostic and therapeutic purposes on images originating from diagnostic examinations with 128-slice spiral computed tomography. Such techniques can be of great significance and find a number of uses in image recognition.

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