Abstract
In Taiwan, breast cancer has become the second leading type of cancerous diseases among women. The incidence and mortality rates keep rising, and mammography remains to be the only effective screening technique which is capable of detecting breast cancer at an early stage. High mammographic density is a strong risk factor for breast cancer. Based on BI-RADS categories, mammograms are classified into four categories (D1-D4) based on the percentage of dense area (PDA). However, reporting of breast density suffers from high inter and intra observer variability. Because the risk of breast cancer is at least three times greater in women with density (D3&D4) than in women with density D1, this paper proposes a local entropy method to identify the higher density (D3&D4) from (D1&D2) by two features. There are 406 mammograms with four categories collected for the test. The higher density (D3&D4) can be identified from lower density (D1&D2) in the correction of 100%. The Az of receiver operating characteristic curve of 0.9996 can be achieved.
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