期刊
CANCER RESEARCH
卷 77, 期 21, 页码 E79-E82出版社
AMER ASSOC CANCER RESEARCH
DOI: 10.1158/0008-5472.CAN-17-0316
关键词
-
类别
资金
- NCI [1U24CA180924-01A1]
- NLM [R01LM011119-01, R01LM009239]
- NCIP/Leidos [14 x 138]
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. (C) 2017 AACR.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据