论文标题
Histomicsml2.0：整个幻灯片成像数据的快速交互式机器学习
HistomicsML2.0: Fast interactive machine learning for whole slide imaging data
论文作者
论文摘要
从全坡度图像中提取定量表型信息为未在开发图像分析算法中经验丰富的研究人员带来了重大挑战。我们提出了新软件，该软件能够对机器学习分类器进行快速学习训练，以检测全扫描成像数据集中的组织学模式。 HistomicsMl2.0使用卷积网络很容易适应各种应用程序，提供了基于Web的用户界面，并且可作为软件容器可用来简化部署。
Extracting quantitative phenotypic information from whole-slide images presents significant challenges for investigators who are not experienced in developing image analysis algorithms. We present new software that enables rapid learn-by-example training of machine learning classifiers for detection of histologic patterns in whole-slide imaging datasets. HistomicsML2.0 uses convolutional networks to be readily adaptable to a variety of applications, provides a web-based user interface, and is available as a software container to simplify deployment.
