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An interpretable classifier for high-resolution breast cancer screening images utilizing weakly supervised localization

机译：一种用于高分辨率乳腺癌筛选图像的可解释分类器利用弱监督定位

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Yiqiu Shen; Nan Wu; Jason Phang; Jungkyu Park; Kangning Liu; Sudarshini Tyagi; Laura Heacock; S. Gene Kim; Linda Moy; Kyunghyun Cho; Krzysztof J. Geras;
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1. Weakly supervised 3D deep learning for breast cancer classification and localization of the lesions in MR images [J] . Zhou Juan, Luo Lu‐Yang, Dou Qi, Journal of magnetic resonance imaging: JMRI . 2019,第4期

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2. Iterative Augmentation of Visual Evidence for Weakly-Supervised Lesion Localization in Deep Interpretability Frameworks: Application to Color Fundus Images [J] . Cristina González-Gonzalo, Bart Liefers, Bram van Ginneken, IEEE Transactions on Medical Imaging . 2020,第11期

机译：深度可解释性框架中弱监督病变定位的迭代增强视觉证据：应用于彩色眼底图像
3. Joint Weakly and Semi-Supervised Deep Learning for Localization and Classification of Masses in Breast Ultrasound Images [J] . Shin Seung Yeon, Lee Soochahn, Yun Il Dong, IEEE Transactions on Medical Imaging . 2019,第3期

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4. Weakly-Supervised Self-Training for Breast Cancer Localization* [C] . Gongbo Liang, Xiaoqin Wang, Yu Zhang, Annual International Conference of the IEEE Engineering in Medicine and Biology Society . 2020

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5. Maximizing the Data Utilization Efficiency in Medical Imaging Diagnosis: From Full Supervision to Weak Supervision [D] . Li, Xiaomeng. 2019

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6. Utilizing Optical Tomography with Ultrasound Localization to Image Heterogeneous Hemoglobin Distribution in Large Breast Cancers [O] . Quing Zhu, Scott H Kurtzman, Poornima Hegde, 2005

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7. Joint Weakly and Semi-Supervised Deep Learning for Localization and Classification of Masses in Breast Ultrasound Images [O] . Seung Yeon Shin, Soochahn Lee, Il Dong Yun, 2019

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An interpretable classifier for high-resolution breast cancer screening images utilizing weakly supervised localization

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