Three-dimensional models provide a more complete view about objects analyzed by considering their depth. Considering the growth of three-dimensional models currently available in Health area, it is necessary to implement efficient query mechanisms that offer alternative ways to locate cases of patients with certain characteristics. Providing a images historical similar to those belonging to the patient can aided the diagnosis offering similar clinical cases. This project aims to develop techniques to recovery three-dimensional medical images based on their content and apply them in the medical context, specifically in the Cardiology area. This project intend to contribute to the detection of anomalies making available similar clinical cases, generating a prototype of query system. To achieve the proposed objectives the following phases are planned: literature review, definition of the database that will be used, extractors and similarity functions implementation, construction of a retrieval system prototype, conduction of tests with medical imaging and analysis of results. The results obtained with the methods developed were positive, in some tests were achieved 90% of accuracy in the search return. It was found that descriptors that took into account the spatial information of the deformations obtained a better result than the methods which analyzed the models from a global perspective. These results confirm the potential of content based retrieval has in the medical context to assist in diagnosis composition as well as contributing to the Computing field in the sense of having developed content based retrieval methods on three-dimensional models domain.
Keywords: 3D CBIR, Congestive Heart Failure, shape descriptors, medical images