Mammographic Computer-Assisted Diagnosis using Computational Statistics Pattern Recognition
نویسندگان
چکیده
منابع مشابه
Significance analysis of qualitative mammographic features, using linear classifiers, neural networks and support vector machines.
Advances in modern technologies and computers have enabled digital image processing to become a vital tool in conventional clinical practice, including mammography. However, the core problem of the clinical evaluation of mammographic tumors remains a highly demanding cognitive task. In order for these automated diagnostic systems to perform in levels of sensitivity and specificity similar to th...
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In this thesis two computer-aided diagnosis (CAD) systems are presented and implemented and their performance is evaluated. The first system proposed is a fully automated segmentation and classification scheme for mammograms based on breast density estimation and detection of asymmetry. First, image preprocessing and segmentation techniques are applied. Then, features for breast density categor...
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Breast cancer is a serious problem, which in the United States causes 43,000 deaths a year, eventually striking 1 in 9 women. Early detection is the only effective countermeasure, and mass mammography screening is the only reliable means for early detection. Mass screening has many shortcomings which could be addressed by a computer-aided mammographic screening system. Accordingly, we have appl...
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In mammographic imaging, the presence of microcalcifications, small deposits of calcium in the breast, is a primary indicator of breast cancer. However, not all microcalcifications are malignant and their distribution within the breast can be used to indicate whether clusters of microcalcifications are benign or malignant. Computer-aided diagnosis (CAD) systems can be employed to help classify ...
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عنوان ژورنال:
- Real-Time Imaging
دوره 1 شماره
صفحات -
تاریخ انتشار 1995