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Computational study demonstrates vector quantization segmentation for detecting masses in mammograms, highlighting computer-aided diagnosis to assist radiologists.
Breast cancer is one of the major causes of death among women. An improvement of early diagnostic techniques is critical for women's quality of life. Mammography is the main test used for screening and early diagnosis. Contrast-enhanced magnetic resonance of the breast is the most attractive alternative to standard mammography. This paper presents a vector quantization segmentation method to detect cancerous mass from mammogram images. In order to increase radiologist's diagnostic performance, several computer-aided diagnosis (CAD) schemes have been developed to improve the detection of primary signatures of this disease: masses and microcalcifications.
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Kekre et al. (2010) studied this question.
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