Computer Aided Diagnosis for Breast Cancer Screening - Piyamas Suapang; Chadaporn Naruephai; Sorawat Chivapreecha (My University, 2016)
Mass segmentation and density classification is an important for breast cancer screening. The purpose of this study is to develop the computer aided diagnosis for mass segmentation and density classification according to the fourth edition of BI-RADS criteria in digital mammography. The digital mammography was digitized high resolution in the image acquisition phase. After the digitization process, an active contour algorithm was applied for mass segmentation. Finally, percentage of mammographic density was calculated for density classification according to the fourth edition of BI-RADS lexicon. The study includes 100 digital mammography of women aged 33-81 years. The results show that the overall accuracy of computerized method classification is 88%.
Keywords: Digitization; Digital Mammography; Breast density; Computer-Aided Diagnosis; AI in cancer detection