A probabilistic network based similiarity measure for cerebral tumors MRI cases retrieval

We propose in this paper a bayesian network based similarity measure for the retrieving of magnetic resonance imaging exams containing cerebral tumors. Bayesian networks proved their efficiency and reliability in several Artificial Intelligence problems and especially in computer aided decision applications. To diagnose a cerebral tumor in a MRI exam, we need to interpret diverse sequences and to refer to visual characteristics and, also, to the patient clinical information such as age, sex, other diseases, etc. Our main idea is argued by the uncertain aspect embodied of the decision making process. This aspect will be translated as a probabilistic decision model. Our work is tested on several medical cases collected from Sahloul Hospital. The retrieval results seem to be promising.