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Rui Yang1, Pei Liu1, Luping Ji1
1School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu 611731, PR China.
本研究引入了一种新的原型驱动的分区 (ProDiv) 方案,以改进病理图像分类中的多个实例学习 (MIL) 的伪袋创建. ProDiv通过优化整个幻灯片图像 (WSI) 的划分来提高分类性能,以便更好地诊断癌症.
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