BlurryScope 通过对模糊图像进行深度学习,实现了用于 HER2 评分的紧,具有成本效益的扫描显微镜
Michael John Fanous1, Christopher Michael Seybold2, Hanlong Chen1,3,4
1Electrical and Computer Engineering Department, University of California, Los Angeles, 90095, CA, USA.
NPJ digital medicine
|August 5, 2025
概括
我们创建了BlurryScope,这是一款低成本,紧的显微镜,使用人工智能进行组织分析. 它在乳腺癌样本中自动进行HER2评分,准确度高,与昂贵的扫描仪相匹配.
科学领域:
- 生物医学工程 生物医学工程
- 计算病理学计算病理学
- 数字健康数字健康
背景情况:
- 组织部分的自动分析对于准确的疾病诊断至关重要.
- 目前的数字病理学扫描仪通常是昂贵的,大型的,许多实验室无法使用.
- 需要具有成本效益的,紧的和自动化的解决方案来进行组织成像和分析.
研究的目的:
- 开发和验证一种新的快速扫描光学显微镜BlurryScope,用于自动化组织切片分析.
- 评估BlurryScope在分类乳腺癌组织中人类表皮生长因子受体2 (HER2) 评分中的性能.
- 为了证明BlurryScope是商业数字病理学扫描仪的可行,低成本的替代方案.
主要方法:
- 开发BlurryScope,这是一个快速扫描光学显微镜,利用连续图像采集和深度学习算法.
- 实现自动化图像拼接,裁剪和HER2分数分类工作流程.
- 对BlurryScope的HER2分类精度与高端数字扫描显微镜进行比较分析.
主要成果:
- BlurryScope的速度与商业数字病理学扫描仪相美,成本显著降低,足迹更小.
- 在动作模糊的免疫组织化学染色乳腺组织部分上进行的自动HER2分类获得了很高的准确性.
- 在284个患者核心中,在4类 (0, 1+, 2+, 3+) 的HER2分类中达到79.3%的准确率,在2类 (0/1+, 2+/3+) 的HER2分类中达到89.7%的准确率.
结论:
- BlurryScope为数字病理学提供了一个具有成本效益的,紧的,自动化的解决方案.
- 该系统在HER2评分方面表现出高精度,可与高端扫描仪相美.
- BlurryScope有可能提高组织分析和癌症诊断的可访问性和效率.
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