Estimating the Number of Significant Canonical Coordinates
Abd-Krim Seghouane, Navid Shokouhi
IEEE Access | Institute of Electrical and Electronics Engineers (IEEE) | Published : 2019
Breast mass is one of the most distinctive signs for the diagnosis of breast cancer, and the accurate segmentation of masses is critical for improving the accuracy of breast cancer detection and reducing the mortality rate. It is time-consuming for a physician to review the film. Besides, traditional medical segmentation techniques often require prior knowledge or manual extraction of features, which often lead to a subjective diagnosis. Therefore, developing an automatic image segmentation method is important for clinical application. In this paper, a fully automatic method based on deep learning for breast mass segmentation is proposed, which combines densely connected U-Net with attention..View full abstract
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Awarded by Australian Research Council
This work was supported by the Australian Research Council under Grant FT 130101394.