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Breast segmentation in MRI: quantitative evaluation of three methods.

, , , , , and . Medical Imaging: Image Processing, volume 8669 of SPIE Proceedings, page 86693G. SPIE, (2013)

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A Comparison Between a Deep Convolutional Neural Network and Radiologists for Classifying Regions of Interest in Mammography., , , , , , , and . Digital Mammography / IWDM, volume 9699 of Lecture Notes in Computer Science, page 51-56. Springer, (2016)Vendor-independent soft tissue lesion detection using weakly supervised and unsupervised adversarial domain adaptation., , , , , and . CoRR, (2018)Automatic Microcalcification Detection in Multi-vendor Mammography Using Convolutional Neural Networks., , , , , and . Digital Mammography / IWDM, volume 9699 of Lecture Notes in Computer Science, page 35-42. Springer, (2016)Towards Accurate Segmentation of Fibroglandular Tissue in Breast MRI Using Fuzzy C-Means and Skin-Folds Removal., , , , , , and . ICIAP (1), volume 9279 of Lecture Notes in Computer Science, page 528-536. Springer, (2015)Improving Breast Cancer Detection Using Symmetry Information with Deep Learning., , and . RAMBO+BIA+TIA@MICCAI, volume 11040 of Lecture Notes in Computer Science, page 90-97. Springer, (2018)Comparison of Four Breast Tissue Segmentation Algorithms for Multi-modal MRI to X-ray Mammography Registration., , , , , , and . Digital Mammography / IWDM, volume 9699 of Lecture Notes in Computer Science, page 493-500. Springer, (2016)Automated linking of suspicious findings between automated 3D breast ultrasound volumes., , , , and . Medical Imaging: Computer-Aided Diagnosis, volume 9785 of SPIE Proceedings, page 97850N. SPIE, (2016)Large scale deep learning for computer aided detection of mammographic lesions., , , , , , , and . Medical Image Anal., (2017)A deep learning method for volumetric breast density estimation from processed full field digital mammograms., , , , and . Medical Imaging: Computer-Aided Diagnosis, volume 10950 of SPIE Proceedings, page 109500F. SPIE, (2019)Automated lesion detection and segmentation in digital mammography using a u-net deep learning network., , , , and . IWBI, volume 10718 of SPIE Proceedings, page 1071805. SPIE, (2018)