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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)

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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)Improving the Automated Detection of Calcifications Using Adaptive Variance Stabilization., , , , , , , and . IEEE Trans. Med. Imaging, 37 (8): 1857-1864 (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)Mammogram denoising to improve the calcification detection performance of convolutional nets., , , , , , , , and . IWBI, volume 10718 of SPIE Proceedings, page 107180W. SPIE, (2018)Automated Labeling of Screening Mammograms with Arterial Calcifications., , , and . Digital Mammography / IWDM, volume 8539 of Lecture Notes in Computer Science, page 589-596. Springer, (2014)LUT-QNE: Look-Up-Table Quantum Noise Equalization in Digital Mammograms., , , , , and . Digital Mammography / IWDM, volume 9699 of Lecture Notes in Computer Science, page 27-34. Springer, (2016)Spatial Enhancement by Dehazing for Detection of Microcalcifications with Convolutional Nets., , , , , , , , and . ICIAP (2), volume 10485 of Lecture Notes in Computer Science, page 288-298. Springer, (2017)Conditional random field modelling of interactions between findings in mammography., , and . Medical Imaging: Computer-Aided Diagnosis, volume 10134 of SPIE Proceedings, page 101341E. SPIE, (2017)The Effect of Mammogram Preprocessing on Microcalcification Detection with Convolutional Neural Networks., , , , , , and . CBMS, page 207-212. IEEE Computer Society, (2017)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)