Saltz Joel, Sharma Ashish, Iyer Ganesh, Bremer Erich, Wang Feiqiao, Jasniewski Alina, DiPrima Tammy, Almeida Jonas S, Gao Yi, Zhao Tianhao, Saltz Mary, Kurc Tahsin
Department of Biomedical Informatics, Stony Brook University, Stony Brook, New York.
Department of Biomedical Informatics, Emory University, Atlanta, Georgia.
Cancer Res. 2017 Nov 1;77(21):e79-e82. doi: 10.1158/0008-5472.CAN-17-0316.
Well-curated sets of pathology image features will be critical to clinical studies that aim to evaluate and predict treatment responses. Researchers require information synthesized across multiple biological scales, from the patient to the molecular scale, to more effectively study cancer. This article describes a suite of services and web applications that allow users to select regions of interest in whole slide tissue images, run a segmentation pipeline on the selected regions to extract nuclei and compute shape, size, intensity, and texture features, store and index images and analysis results, and visualize and explore images and computed features. All the services are deployed as containers and the user-facing interfaces as web-based applications. The set of containers and web applications presented in this article is used in cancer research studies of morphologic characteristics of tumor tissues. The software is free and open source. .
精心策划的病理学图像特征集对于旨在评估和预测治疗反应的临床研究至关重要。研究人员需要从患者到分子尺度跨多个生物学尺度综合的信息，以便更有效地研究癌症。本文描述了一套服务和网络应用程序，这些程序允许用户在全切片组织图像中选择感兴趣的区域，在选定区域上运行分割管道以提取细胞核并计算形状、大小、强度和纹理特征，存储和索引图像及分析结果，以及可视化和探索图像与计算出的特征。所有服务都作为容器进行部署，而面向用户的界面则作为基于网络的应用程序。本文介绍的容器和网络应用程序集用于肿瘤组织形态学特征的癌症研究。该软件是免费且开源的。
