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This paper is a part of a complex study of developing methods for semantic interpretation of medical images, to permit the semi-automatic diagnosis. The first objective of the study is to develop new methods for medical image segmentation and a set of visual features. The second objective consists of developing a unifying framework for semantic images annotation, to be used in the process of medical diagnosis. The developed diagnosis method is based on on semantic pattern rules capable to discover associations between visual features of medical images and their diagnoses. Although we present the results achieved in endoscopic images analysis, our methods can be used to analyze other types of medical images. The prototype system was applied to real datasets and the results show high accuracy.