Support vector machine learning for detection of microcalcifications in mammograms
Proceedings IEEE International Symposium on Biomedical Imaging - Trang 201-204
Tóm tắt
Microcalcification (MC) clusters in mammograms can be an indicator of breast cancer. In this work we propose for the first time the use of support vector machine (SVM) learning for automated detection of MCs in digitized mammograms. In the proposed framework, MC detection is formulated as a supervised-learning problem and the method of SVM is employed to develop the detection algorithm. The proposed method is developed and evaluated using a database of 76 mammograms containing 1120 MCs. To evaluate detection performance, free-response receiver operating characteristic (FROC) curves are used. Experimental results demonstrate that, when compared to several other existing methods, the proposed SVM framework offers the best performance.
Từ khóa
#Support vector machines #Machine learning #Support vector machine classification #Breast cancer #Risk management #Radiology #Detection algorithms #Databases #Calcium #Breast tissueTài liệu tham khảo
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