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Breast cancer is the most common malignant disease in women. Mammographic mass retrieval system can help radiologists to improve the diagnostic accuracy by retrieving biopsy-proven masses which are similar with the diagnostic ones. However, although screening mammograms usually consists of two-view(MLO and CC) mammography of the same breast, most breast CAD systems incorporate with image retrieval...
The classification of breast masses into benign and malignant categories plays an important role in the area of computer-aided diagnosis (CAD) of breast cancer. In this paper, one novel scheme based on multi-view information fusion is proposed, in order to improve the accuracy and the robustness of the classification and reduce the false positive rates. Five contour and shape features of the masses...
The classification of breast masses into benign and malignant categories plays an important role in the area of computer-aided diagnosis (CAD) of breast cancer. In this paper, in order to improve the accuracy and the robustness of the classification and reduce the false positive rates, we proposed one novel scheme that was based on information fusion in multi views. A series of contour and shape features...
The purpose of this study is to investigate the significance of the multi-agent interactive information fusion algorithm over the matter of identification of breast masses in digitized images. For the lack of enough correlation information between the individual classifiers, the generalization performance of the Bayesian fusion method is sometimes far from the expected level, and thereby the multi-agent...
Clustered microcalcification is an important signal for breast cancer in the early stages. In this paper, we propose a multiple kernel SVM with group features (GF-SVM) to tackle problems associated with heterogeneous features of clustered microcalcification and normal breast tissues in suspicious regions. Specifically, different types of features such as being gradient, geometric and textural are...
Mammography is one of the most effective detection methods of breast cancer. A novel algorithm was proposed to segment the pectoral muscle automatically. It firstly carried out a series of ROIs upon the neighborhood, and in each ROI, the optimal threshold was computed with the iterative thresholding. After combining these thresholds into an optimal threshold curve and computing the corresponding local...
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