Large scale deep learning for computer aided detection of mammographic lesions von Kooi, Thijs, Litjens, Geert, van Ginneken, Bram, Gubern-Mérida, Albert, Sánchez, Clara I., Mann, Ritse, den Heeten, Ard, Karssemeijer, Nico

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Using deep learning to assist readers during the arbitration process: a lesion-based retrospective evaluation of breast cancer screening performance von Kerschke, Laura, Weigel, Stefanie, Rodriguez-Ruiz, Alejandro, Karssemeijer, Nico, Heindel, Walter

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Discriminating solitary cysts from soft tissue lesions in mammography using a pretrained deep convolutional neural network von Kooi, Thijs, Ginneken, Bram, Karssemeijer, Nico, Heeten, Ard

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Stain Specific Standardization of Whole-Slide Histopathological Images von Ehteshami Bejnordi, Babak, Litjens, Geert, Timofeeva, Nadya, Otte-Holler, Irene, Homeyer, Andre, Karssemeijer, Nico, van der Laak, Jeroen Awm

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Location Sensitive Deep Convolutional Neural Networks for Segmentation of White Matter Hyperintensities von Ghafoorian, Mohsen, Karssemeijer, Nico, Heskes, Tom, van Uden, Inge W. M., Sanchez, Clara I., Litjens, Geert, de Leeuw, Frank-Erik, van Ginneken, Bram, Marchiori, Elena, Platel, Bram

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Breast image analysis for risk assessment, detection, diagnosis, and treatment of cancer von Giger, Maryellen L, Karssemeijer, Nico, Schnabel, Julia A

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Impact of artificial intelligence support on accuracy and reading time in breast tomosynthesis image interpretation: a multi-reader multi-case study von van Winkel, Suzanne L., Rodríguez-Ruiz, Alejandro, Appelman, Linda, Gubern-Mérida, Albert, Karssemeijer, Nico, Teuwen, Jonas, Wanders, Alexander J. T., Sechopoulos, Ioannis, Mann, Ritse M.

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Using deep convolutional neural networks to identify and classify tumor-associated stroma in diagnostic breast biopsies von Ehteshami Bejnordi, Babak, Mullooly, Maeve, Pfeiffer, Ruth M., Fan, Shaoqi, Vacek, Pamela M., Weaver, Donald L., Herschorn, Sally, Brinton, Louise A., van Ginneken, Bram, Karssemeijer, Nico, Beck, Andrew H., Gierach, Gretchen L., van der Laak, Jeroen A. W.M., Sherman, Mark E.

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Classifying symmetrical differences and temporal change for the detection of malignant masses in mammography using deep neural networks von Kooi, Thijs, Karssemeijer, Nico

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Automated Detection of DCIS in Whole-Slide H&E Stained Breast Histopathology Images von Ehteshami Bejnordi, Babak, Balkenhol, Maschenka, Litjens, Geert, Holland, Roland, Bult, Peter, Karssemeijer, Nico, van der Laak, Jeroen A. W. M.

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Volumetric breast density affects performance of digital screening mammography von Wanders, Johanna O. P., Holland, Katharina, Veldhuis, Wouter B., Mann, Ritse M., Pijnappel, Ruud M., Peeters, Petra H. M., van Gils, Carla H., Karssemeijer, Nico

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Volumetric breast density estimation from full-field digital mammograms: a validation study von Gubern-Mérida, Albert, Kallenberg, Michiel, Platel, Bram, Mann, Ritse M, Martí, Robert, Karssemeijer, Nico

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Influence of Risk Category and Screening Round on the Performance of an MR Imaging and Mammography Screening Program in Carriers of the BRCA Mutation and Other Women at Increased R... von Vreemann, Suzan, Gubern-Mérida, Albert, Schlooz-Vries, Margrethe S, Bult, Peter, van Gils, Carla H, Hoogerbrugge, Nicoline, Karssemeijer, Nico, Mann, Ritse M

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Deep multi-scale location-aware 3D convolutional neural networks for automated detection of lacunes of presumed vascular origin von Ghafoorian, Mohsen, Karssemeijer, Nico, Heskes, Tom, Bergkamp, Mayra, Wissink, Joost, Obels, Jiri, Keizer, Karlijn, de Leeuw, Frank-Erik, Ginneken, Bram van, Marchiori, Elena, Platel, Bram

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Context-aware stacked convolutional neural networks for classification of breast carcinomas in whole-slide histopathology images von Bejnordi, Babak Ehteshami, Zuidhof, Guido, Balkenhol, Maschenka, Hermsen, Meyke, Bult, Peter, van Ginneken, Bram, Karssemeijer, Nico, Litjens, Geert, van der Laak, Jeroen

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Clinical evaluation of a computer-aided diagnosis system for determining cancer aggressiveness in prostate MRI von Litjens, Geert J. S., Barentsz, Jelle O., Karssemeijer, Nico, Huisman, Henkjan J.

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Multireader Study on the Diagnostic Accuracy of Ultrafast Breast Magnetic Resonance Imaging for Breast Cancer Screening von van Zelst, Jan C.M, Vreemann, Suzan, Witt, Hans-Joerg, Gubern-Merida, Albert, Dorrius, Monique D, Duvivier, Katya, Lardenoije-Broker, Susanne, Lobbes, Marc B.I, Loo, Claudette, Veldhuis, Wouter, Veltman, Jeroen, Drieling, Daniel, Karssemeijer, Nico, Mann, Ritse M

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The effect of volumetric breast density on the risk of screen-detected and interval breast cancers: a cohort study von Wanders, Johanna O P, Holland, Katharina, Karssemeijer, Nico, Peeters, Petra H M, Veldhuis, Wouter B, Mann, Ritse M, van Gils, Carla H

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A new 2D segmentation method based on dynamic programming applied to computer aided detection in mammography von Timp, Sheila, Karssemeijer, Nico

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Influence of breast compression pressure on the performance of population-based mammography screening von Holland, Katharina, Sechopoulos, Ioannis, Mann, Ritse M, den Heeten, Gerard J, van Gils, Carla H, Karssemeijer, Nico

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