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This work is about the investigation of digital image segmentation techniques (characteristics, problems and main solutions) for specific application in mammography, with the objective of aiding microcalcifications detection. The identification of the structure type on mammogram evaluation is an important requirement to prepare the diagnosis, because of its peculiarities when associate to breast cancer. As nowadays more and more CAD (Computer-aided diagnosis) are being developed in arder to, starting from the convenient digital image processing, classify the finding structures as an aid to the diagnosis of breast cancer, it is of fundamental importance that the images segmentation has enough quality to allow the effectiveness of the structures classification. Particularly, cases of dense breast represent an additional and very important difficulty for the diagnosis, beca use of the peculiar characteristics of the image in terms of bad contrast, due to the existence significantly larger of fibrous tissue, which hinder the identification of suspicious signs in breast image. Therefore, this work focus one the extensive study of the main segmentation techniques developed to mammographic images in arder to determine which are more efficient in the microcalcifications extraction process.

Segmentação de imagens mamográficas digitais para detecção de microcalcificações em mamas densas