论文笔记 | 基于深度学习的乳腺转移瘤识别（Deep Learning for Identifying Metastatic Breast Cancer）
论文阅读笔记：原文链接 摘要 生物医学图像国际研讨会（International Symposium on Biomedical Imaging，ISBI）举办了一个在前哨淋巴节点全幻灯图中自动检测转移性乳腺癌的挑战赛。 该队全幻灯图分类准确AUC准确率为0.925，癌细胞定位得分为0.7051。病理学家的分类AUC准确率为0.966，癌细胞定位得分为0.733。 将病理学家诊断和深度学习系统预测
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- 1. 论文阅读《Deep Learning for Identifying Metastatic Breast Cancer》
- 2. 论文笔记 / Deep features for breast cancer histopathological image classification
- 3. 论文阅读《Deep Learning Assessment of Tumor Proliferation in Breast Cancer Histological Images》
- 4. Grand Challenge on Breast Cancer Histology Images
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