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深度监督两阶段生成对抗网络:解决组织病理图像染色归一化难题
同时,研究使用了多个公开的数据集,如肿瘤增殖评估挑战(TUPAC-2016)数据集、有丝分裂和异型性 14(MITOS-ATYPIA-14)挑战数据集等。 下面来看看具体的研究结果: 染色归一化图像质量评估:研究人员分别在多个数据集上训练染色归一化模型,采用结构相似性 ...
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