勤益科大機構典藏:Item 987654321/7083
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    题名: Pectoral Muscle Segmentation for Digital Mammograms Based on Otsu Thresholding
    作者: 劉正忠
    贡献者: 電子工程(學)系
    日期: 2012-04
    上传时间: 2018-01-07 13:43:09 (UTC+8)
    摘要: The appearance of pectoral muscle in medio-lateral oblique (MLO) views of mammograms can increase the false positive in computer aided detection (CAD) of breast cancer detection. Pectoral muscle has to be identified and segmented from the breast region in a mammogram before further analysis. The main goal of this paper is to propose an accurate and efficient algorithm of pectoral muscle extraction on MLO mammograms. The proposed algorithm bases on the positional characteristic of pectoral muscle in a breast region to combine the iterative Otsu thresholding scheme and the mathematic morphological processing to find the rough border of the pectoral muscle. The multiple regression analysis is then employed on the rough border to obtain the accurate segmentation of the pectoral muscle. The presented algorithm is tested on the digital mammograms from the Mammogram Image Analysis Society (MIAS) database. The experimental results show that the pectoral muscle extracted by the presented algorithm approximately follows that extracted by an expert radiologist.
    關聯: Applied Mechanics and Materials
    显示于类别:[電子工程系(所)] 【電子工程系所】期刊論文

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