Computer image understanding applied to medical diagnosis – an outline of the concept
Journal Title: Inżynier i Fizyk Medyczny - Year 2014, Vol 3, Issue 1
Abstract
The concept of computer understanding of medical images was presented. So-called seons were proposed to create model of diagnostically significant image content. The effect of mental cognition was considered with ability of visual perception to recognize information in the context of specific domain knowledge (e.g. conditions of a specific disease) and clinical data (i.e. results of general or specialistic examinations, other diagnosis, risk factors, etc.). Therefore, the research purpose was integration of the numerical representation of imaged diagnostic information with the formal model of domain knowledge (i.e. ontology) and the model of image subjective cognition by experts. All these issues relate to specific clinical tasks. This integrated model is optimized with the criterion of maximum extraction of formal components of content (represented by set of seons), which have a crucial role in the understanding and interpretation of the images. Computational components become diagnostically important due to the verification of their usefulness in the subjective clinical tests. However, computational patterns and relevant norms/metrics that allow to detect the essential components for a complete lack of visual perception according to classical procedures are sought. Moreover, discussed method of understanding the recorded image data was adjusted to methodology of computer-aided diagnosis (CAD) in medicine. Two important clinical applications, including acute stroke diagnosis with the computed tomography imaging (CT), and recognition of breast cancer in mammograms were indicated to illustrate possible applications.
Authors and Affiliations
Artur Przelaskowski
Keywords
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