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机译:全幻灯肺癌图像分析弱监督深度学习
Department of Computer Science and Engineering The Chinese University of Hong Kong Hong Kong China;
Department of AI Image Research Imsight Medical Technology Company Ltd. Shenzhen China;
Hexian Memorial Hospital Southern Medical University Guangzhou China;
Department of Computer Science and Engineering The Chinese University of Hong Kong Hong Kong China;
Department of Computing Imperial College London London U.K.;
Department of AI Image Research Imsight Medical Technology Company Ltd. Shenzhen China;
State Key Laboratory of Oncology in South China Collaborative Innovation Center for Cancer Medicine Sun Yat-sen University Cancer Center Guangzhou China;
State Key Laboratory of Oncology in South China Collaborative Innovation Center for Cancer Medicine Sun Yat-sen University Cancer Center Guangzhou China;
Department of Computer Science and Engineering The Chinese University of Hong Kong Hong Kong China;
Cancer; Lung; Feature extraction; Tumors; Task analysis; Supervised learning; Image analysis;
机译:临床级计算病理在整个幻灯片图像上使用弱监督深度学习
机译:临床级计算病理在整个幻灯片图像上使用弱监督深度学习
机译:弱视3D深入学习乳腺癌分类和MR图像病变的定位
机译:基于弱监督的整个幻灯片图像上肺癌自动分类的框架
机译:肺癌诊断和乳腺癌风险分析的深度学习方法与手工制作功能。
机译:使用深度学习对肺癌分类的弱监督学习
机译:基于深度学习的肺癌六型分类器,具有组织病理整体幻灯片的肺癌和模仿图像:回顾性研究