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Chest wall segmentation in automated 3D breast ultrasound scans.

, , , , and . Medical Image Analysis, 17 (8): 1273-1281 (2013)

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MRI to X-ray mammography intensity-based registration with simultaneous optimisation of pose and biomechanical transformation parameters., , , , , , , , , and 2 other author(s). Medical Image Analysis, 18 (4): 674-683 (2014)Automated soft tissue lesion detection and segmentation in digital mammography using a u-net deep learning network., , , and . CoRR, (2018)Breast parenchyma analysis and classification for breast masses detection using texture feature descriptors and neural networks in dedicated breast CT images., , , and . Medical Imaging: Computer-Aided Diagnosis, volume 10950 of SPIE Proceedings, page 109500J. SPIE, (2019)Vendor-independent soft tissue lesion detection using weakly supervised and unsupervised adversarial domain adaptation., , , , , and . Medical Imaging: Computer-Aided Diagnosis, volume 10950 of SPIE Proceedings, page 1095002. 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)Deep Learning Framework for Digital Breast Tomosynthesis Reconstruction., , , , , and . CoRR, (2018)MRI-based visualization and augmented reality for breast surgery planning and guidance., , , , , , , , and . CURAC, page 285-286. (2015)Vendor-independent soft tissue lesion detection using weakly supervised and unsupervised adversarial domain adaptation., , , , , and . CoRR, (2018)Towards Spatial Correspondence between Specimen and In-vivo Breast Imaging., , , , , , , , and . Digital Mammography / IWDM, volume 8539 of Lecture Notes in Computer Science, page 674-680. Springer, (2014)Chest wall segmentation in automated 3D breast ultrasound scans., , , , and . Medical Image Analysis, 17 (8): 1273-1281 (2013)