Clinical grade computional pathology using weakly supervised deep learning on whole slide images
Abstract 需要大量手工标注数据集一直阻碍病理学方面的决策支持系统的发展以及在临床上部署。为了解决这一问题，本文提出了基于多实例学习的深度学习系统，其仅仅使用已报告的诊断作为训练的标签，得意边广泛且费时间的逐像素手工标注。本文在来自15187位病人的44732张全切片图像构成的数据集上评估了该框架的性能，并且这些数据没有经过任何整理(curation)。前列腺癌、基底细胞癌和乳腺癌转移到腋窝
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相关文章
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