Automated Identification of Clustered Microcalcifications in Digital Mammography(International Forum on Medical Imaging in Asia 2009 (IFMIA 2009))

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概要

• 論文の詳細を見る

• Computer-aided diagnosis(CAD) system for early diagnosis of breast cancer has been developed as a useful tool for radiologists since many years. However, the commercial product can identify part of lesion in detecting microcalcification. In this study, we used gray level co-occurrence matrix(GLCM) to extract texture features. Fourteen features are analyzed and some of them are selected which are more significant for classification. Afterwards, support vector machine(SVM) has been used to perform a nonlinear classification. The accuracy of proposed system is 90.44%, the sensitivity is 73.53%, and the specificity is 93.82%.

• 社団法人電子情報通信学会の論文
• 2009-01-12

著者

• Tsai Po-pang

  Department Of Radiology China Medical University Hospital

• Huang Yi-Jhe

  Graduate Institute of Clinical Medical Science, China Medical University

• Cheng Da-Chuan

  Department of Biomedical Imaging and Radiological Science, China Medical University

• Shen Wu-Chung

  Department of Radiology, China Medical University Hospital

• Huang Yi-jhe

  Graduate Institute Of Clinical Medical Science China Medical University

• Shen Wu-chung

  Department Of Radiology China Medical University Hospital

• Cheng Da-chuan

  Department Of Biomedical Imaging And Radiological Science China Medical University

関連論文

• Automated Identification of Clustered Microcalcifications in Digital Mammography(International Forum on Medical Imaging in Asia 2009 (IFMIA 2009))

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