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Automated soft tissue lesion detection and segmentation in digital mammography using a u-net deep learning network.

, , , and . CoRR, (2018)

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Automated soft tissue lesion detection and segmentation in digital mammography using a u-net deep learning network., , , and . CoRR, (2018)Can radiologists improve their breast cancer detection in mammography when using a deep learning based computer system as decision support?, , , , and . IWBI, volume 10718 of SPIE Proceedings, page 1071803. SPIE, (2018)Phantom-based comparison of microcalcification visibility between digital and synthetic mammography using humans and a deep neural network as observers., , , and . IWBI, volume 10718 of SPIE Proceedings, page 1071810. SPIE, (2018)How does wide-angle breast tomosynthesis depict calcifications in comparison to digital mammography? A retrospective observer study., , , , , , , and . IWBI, volume 10718 of SPIE Proceedings, page 107181T. SPIE, (2018)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)Pectoral muscle segmentation in breast tomosynthesis with deep learning., , , , , , and . Medical Imaging: Computer-Aided Diagnosis, volume 10575 of SPIE Proceedings, page 105752J. SPIE, (2018)