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A Comparison Between a Deep Convolutional Neural Network and Radiologists for Classifying Regions of Interest in Mammography., , , , , , , и . Digital Mammography / IWDM, том 9699 из Lecture Notes in Computer Science, стр. 51-56. Springer, (2016)Vendor-independent soft tissue lesion detection using weakly supervised and unsupervised adversarial domain adaptation., , , , , и . CoRR, (2018)Automatic Microcalcification Detection in Multi-vendor Mammography Using Convolutional Neural Networks., , , , , и . Digital Mammography / IWDM, том 9699 из Lecture Notes in Computer Science, стр. 35-42. Springer, (2016)Towards Accurate Segmentation of Fibroglandular Tissue in Breast MRI Using Fuzzy C-Means and Skin-Folds Removal., , , , , , и . ICIAP (1), том 9279 из Lecture Notes in Computer Science, стр. 528-536. Springer, (2015)Comparison of Four Breast Tissue Segmentation Algorithms for Multi-modal MRI to X-ray Mammography Registration., , , , , , и . Digital Mammography / IWDM, том 9699 из Lecture Notes in Computer Science, стр. 493-500. Springer, (2016)Improving Breast Cancer Detection Using Symmetry Information with Deep Learning., , и . RAMBO+BIA+TIA@MICCAI, том 11040 из Lecture Notes in Computer Science, стр. 90-97. Springer, (2018)Automated linking of suspicious findings between automated 3D breast ultrasound volumes., , , , и . Medical Imaging: Computer-Aided Diagnosis, том 9785 из SPIE Proceedings, стр. 97850N. SPIE, (2016)Large scale deep learning for computer aided detection of mammographic lesions., , , , , , , и . Medical Image Anal., (2017)A deep learning method for volumetric breast density estimation from processed full field digital mammograms., , , , и . Medical Imaging: Computer-Aided Diagnosis, том 10950 из SPIE Proceedings, стр. 109500F. SPIE, (2019)Breast MRI and X-ray mammography registration using gradient values., , , , , , , и . Medical Image Anal., (2019)