Ruriha Yoshikawa

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Architectural distortion in mammography is the most missing finding for radiologists, despite high malignancy. Many research groups have developed methods for automated detection of architectural distortion. However, improvement of their detection performance is desired. In this study, we developed a novel method for automated detection of architectural(More)
X-ray breast computed tomography (breast CT) was developed by some research groups to overcome the limitations of mammography. Breast CT is expected to be an effective diagnostic tool because it can generate three-dimensional images of a breast. However, the spatial resolution of the existing system is not satisfactory for identifying microcalcifications(More)
ABSTRUCT Breast cancer is a serious health concern for all women. Computer-aided detection for mammography has been used for detecting mass and micro-calcification. However, there are challenges regarding the automated detection of the architectural distortion about the sensitivity. In this study, we propose a novel automated method for detecting(More)
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