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Reducing False-Positive Biopsies using Deep Neural Networks that Utilize both Local and Global Image Context of Screening Mammograms |
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| Authors: | Wu Nan Huang Zhe Shen Yiqiu Park Jungkyu Phang Jason Makino Taro Gene Kim S Cho Kyunghyun Heacock Laura Moy Linda Geras Krzysztof J |
| Institution: | 1.Center for Data Science, New York University, New York City, USA ;2.Department of Radiology, New York University School of Medicine, New York City, USA ;3.Perlmutter Cancer Center, NYU Langone Health, New York City, USA ;4.Center for Advanced Imaging Innovation and Research, NYU Langone Health, New York City, USA ;5.Department of Computer Science, Courant Institute of Mathematical Sciences, New York University, New York City, USA ;6.CIFAR Associate Fellow, New York City, USA ; |
| Abstract: | Journal of Digital Imaging - Breast cancer is the most common cancer in women, and hundreds of thousands of unnecessary biopsies are done around the world at a tremendous cost. It is crucial to... |
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