A software tool for automatic identification in medical images should allow the identification of anatomical structures ^ and the presence of abnormalities in these structures, such as malformations and tumors. The automation of these tasks would help to decrease the time required for decision making in routine diagnosis and surgical planning. We have addressed the problem of identification of medical structures using a multiscale approach, the scale space, combined with a matching procedure that uses a priori information. The method can be divided in three steps: 1) construction of the linear scale space; 2) application of a feature detector that leads to a multiscale representation based on them; and 3) matching the elements present in the structure built in step 2 with a known pattern that describes the structure under study. We have built an application that uses geometrical information on the desired feature and its relations with other features present in the scene. Results have shown the method's ability to identify medical structures at several levels of resolution and noise. The method allows the generation of specific patterns to be matched by the target-structure with different diseases from a medical database. 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University of UtrechtThe Netherlands