Abstract
Medical images such as X-ray images, ultrasonic images and CT-images provide the phisician with a great deal of valuable information that is useful in the making of a diagnosis. It is often unclear, however, which facets or items of these images are most valuable, how much weight should be given to each item, and how diagnostic logic can be used with these items. In this paper, fuzziness in imaging data and in the diagnostic process are studied, and then diagnostic logic based on imaging data using fuzzy inference is discussed. Fuzzy chracteristics are first encountered in imaging data in the process of scaling the degree of the imaging features. The criteria for evaluation of each item differ from doctor to doctor. Judgement becomes subjective. Fuzziness also exists in the diagnostic logic for imaging because its framework cannot be clearly defined, since it is changed by the images chosen and these choices are somewhat subjectively made. Moreover, the weights of these items do not always remain constant.
