BlurryScope：利用模糊图像的深度学习实现紧凑、经济高效的扫描显微镜用于HER2评分
BlurryScope enables compact, cost-effective scanning microscopy for HER2 scoring using deep learning on blurry images
AI总结：
BlurryScope利用连续采集和深度学习，在模糊图像上实现紧凑经济的HER2评分，测试准确率达79.3%（4类）和89.7%（2类），媲美高端扫描仪。
摘要：
我们开发了一种名为“BlurryScope”的快速扫描光学显微镜，该显微镜利用连续图像采集和深度学习，为组织切片的自动检查和分析提供了一种经济高效且紧凑的解决方案。该设备在速度上与商用数字病理扫描仪相当，但价格显著更低，体积和重量也更小。使用BlurryScope，我们在免疫组织化学（IHC）染色的乳腺组织切片的运动模糊图像上实现了人表皮生长因子受体2（HER2）评分的自动分类，其结果与使用高端数字扫描显微镜获得的结果一致。使用包含284个独特患者核心的测试集，我们在4类（0、1+、2+、3+）和2类（0/1+、2+/3+）HER2分类中分别达到了79.3%和89.7%的测试准确率。BlurryScope自动化了整个工作流程，从图像扫描到拼接和裁剪，以及HER2评分分类。
英文摘要：
We developed a rapid scanning optical microscope, termed "BlurryScope", that leverages continuous image acquisition and deep learning to provide a cost-effective and compact solution for automated inspection and analysis of tissue sections. This device offers comparable speed to commercial digital pathology scanners, but at a significantly lower price point and smaller size/weight. Using BlurryScope, we implemented automated classification of human epidermal growth factor receptor 2 (HER2) scores on motion-blurred images of immunohistochemically (IHC) stained breast tissue sections, achieving concordant results with those obtained from a high-end digital scanning microscope. Using a test set of 284 unique patient cores, we achieved testing accuracies of 79.3% and 89.7% for 4-class (0, 1+, 2+, 3+) and 2-class (0/1+, 2+/3+) HER2 classification, respectively. BlurryScope automates the entire workflow, from image scanning to stitching and cropping, as well as HER2 score classification.
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