An Efficient Hybrid Detection System for Abnormal Masses in Digital and Analog Mammogram

Mammography is a type of radiography used on the breasts as screening method for women. The indicators for breast cancer aremasses and calcifications. Breast cancer screenings show that radiologists miss 8%–20% of the tumors. For this reason, development of systems for computer-aided detection (CAD) and computer-aided diagnosis (CADx) algorithms is the concern of a lot of researches currently being done. CAD and CADx algorithms assist radiologists in the decision between follow up and biopsy phases. An intelligent Image Processing Technique employed in systems that can help the radiology in detecting abnormal masses. This paper presents a general framework for mammography that will provide advantages for managing information and simplifying process in each layer for imaging technique. A method has been developed to make supporting tools used a framework as a reference model. This method will automatically segment and detect abnormal masses in analog and digital mammography images and compare between results.

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