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Improving the automated detection of calcifications by combining deep cascades and deep convolutional nets.

, , , , , , and . IWBI, volume 10718 of SPIE Proceedings, page 1071808. SPIE, (2018)

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Experiments with radiologists and a fully automated method for characterization of microcalcification clusters., , and . CARS, volume 1230 of International Congress Series, page 586-592. Elsevier, (2001)Deep learning of symmetrical discrepancies for computer-aided detection of mammographic masses., and . Medical Imaging: Computer-Aided Diagnosis, volume 10134 of SPIE Proceedings, page 101341J. SPIE, (2017)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)Automated Detection of DCIS in Whole-Slide H&E Stained Breast Histopathology Images., , , , , , and . IEEE Trans. Medical Imaging, 35 (9): 2141-2150 (2016)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)Gray-scale and geometric registration of full-field digital and film-screen mammograms., and . Medical Image Anal., 11 (2): 146-156 (2007)Discrete dynamic contour model for mass segmentation in digital mammograms., , and . Medical Imaging: Image Processing, volume 3661 of SPIE Proceedings, SPIE, (1999)The use of contextual information for computer aided detection of masses in mammograms., and . Medical Imaging: Computer-Aided Diagnosis, volume 7260 of SPIE Proceedings, page 72600Q. SPIE, (2009)Estimating corresponding locations in ipsilateral breast tomosynthesis views., , and . Medical Imaging: Computer-Aided Diagnosis, volume 7963 of SPIE Proceedings, page 796306. SPIE, (2011)Deep Multi-scale Location-aware 3D Convolutional Neural Networks for Automated Detection of Lacunes of Presumed Vascular Origin., , , , , , , , , and 1 other author(s). CoRR, (2016)