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Content-Based Image Retrieval CBIR aims to retrieval, in an image database, the most similar occurrences to an image provided as a query, from extracted characteristics of these objects. The use of CBIR concept, although exploited for recovery of twodimensional images, is still under explored in the three-dimensional objects knowledge field. Based on the identification of the current literature gaps regarding efficient approaches to retrieval these objects, the objective of this study was to define, implement and validate retrieval techniques of three-dimensional medical objects based on their content considering global and regionalized searches of the three-dimensional structure. In order to achieve this objective, the following activities were carried out: literature review, database definition, implementation of descriptors and methods of comparison by similarity, construction of a retrieval system prototype, tests with three-dimensional medical objects and results analysis. The results obtained with the methods developed were positive, reaching 90% of mean precision in the return of the search. It has been found that the descriptors based on Spherical Harmonics can be adapted to be used as local descriptors. Additionally, it was identified that the approach using bipartite graphs in conjunction with the similarity computation through network flow, produced better results than the methods that used classic approaches of comparison. Regarding the case study analyzed, the Cardiomyopathies, it was possible to verify that the information of age and gender contribute to improve the accuracy of the retrieval, since this information can directly influence the structure of the left ventricle. In addition, in an evaluation with end users of Cardiology area, it was verified that this approach can effectively aid in the diagnoses. These results confirmed the potential that content-based retrieval has in the medical context, as well as contribute to the Computing area in the sense of developing techniques for content-based in three-dimensional retrieval.

Recuperação de objetos médicos 3D utilizando harmônicos esféricos e redes de fluxo.