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When the endoscopist is exploring the digestive cavity, the action of focusing on a particular organ area and of evoking diagnostic hypotheses underlies a complex march of the thought. This mind process has to be analyzed in terms of data fusion and of reasoning in order to lay foundations with a view to a computerized expert system in endoscopy. Provided with evolved functionalities (the similar case retrieval and the diagnostic hypothesis evaluation), a digestive endoscopy atlas can be used as a tool for training and even as a diagnostic aid for "junior" endoscopists. The architecture of such a system is to have its basis in Case Based Reasoning (CBR), organized around two bases, one of endoscopic knowledge and one of case iconography. The retrieval of similar cases can be assimilated by a fusion process with two steps, classification (global method) owing to the knowledge base and, afterwards, measurement (local method) by means of selected cases of the endoscopic case base. Lesion identification and Disease recognition - that, is, the Scene analyze - are the driving forces not only in the Classification stage, but also in the Similarity measure stage. Besides, classification algorithms, tested on simulated endoscopic descriptions, afford results full of promise.