Automatic Segmentation of the Dense Tissue in Digital Mammograms for BIRADS Density Categorization
نویسندگان
چکیده
Currently, the Breast Imaging Reporting and Data System (BIRADS) density categorization is the most popular tool for density assessment among radiologists. However, it is subject to interobserver variabilities. Therefore, different automated methods have been proposed for dense tissue segmentation. In [1], a technique based on modeling of breast tissue using a Gaussian mixture model was proposed to segment the fibroglandular tissue in digitized mammograms. We modified and extended this method to segment the dense tissue in digital mammograms and then classified them to different BIRADS density categories.
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تاریخ انتشار 2017