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Developing the Quantitative Histopathology Image Ontology (QHIO): A case study using the hot spot detection problem.开发定量组织病理学图像本体(QHIO):以热点检测问题为例的研究
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Identifying in vivo DCE MRI markers associated with microvessel architecture and gleason grades of prostate cancer.识别与前列腺癌微血管结构和Gleason分级相关的活体动态对比增强磁共振成像(DCE MRI)标志物。
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癌症研究的图像分析资源:用于可视化、分析和管理的PIIP-病理学图像信息学平台。

An Image Analysis Resource for Cancer Research: PIIP-Pathology Image Informatics Platform for Visualization, Analysis, and Management.

作者信息

Martel Anne L, Hosseinzadeh Dan, Senaras Caglar, Zhou Yu, Yazdanpanah Azadeh, Shojaii Rushin, Patterson Emily S, Madabhushi Anant, Gurcan Metin N

机构信息

Sunnybrook Research Institute, Toronto, Canada.

Medical Biophysics, University of Toronto, Toronto, Canada.

出版信息

Cancer Res. 2017 Nov 1;77(21):e83-e86. doi: 10.1158/0008-5472.CAN-17-0323.

DOI:10.1158/0008-5472.CAN-17-0323
PMID:29092947
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5679396/
Abstract

Pathology Image Informatics Platform (PIIP) is an NCI/NIH sponsored project intended for managing, annotating, sharing, and quantitatively analyzing digital pathology imaging data. It expands on an existing, freely available pathology image viewer, Sedeen. The goal of this project is to develop and embed some commonly used image analysis applications into the Sedeen viewer to create a freely available resource for the digital pathology and cancer research communities. Thus far, new plugins have been developed and incorporated into the platform for out of focus detection, region of interest transformation, and IHC slide analysis. Our biomarker quantification and nuclear segmentation algorithms, written in MATLAB, have also been integrated into the viewer. This article describes the viewing software and the mechanism to extend functionality by plugins, brief descriptions of which are provided as examples, to guide users who want to use this platform. PIIP project materials, including a video describing its usage and applications, and links for the Sedeen Viewer, plug-ins, and user manuals are freely available through the project web page: http://pathiip.org .

摘要

病理图像信息学平台(PIIP)是一项由美国国家癌症研究所/美国国立卫生研究院赞助的项目,旨在管理、注释、共享和定量分析数字病理成像数据。它是在现有的免费病理图像查看器Sedeen的基础上进行扩展的。该项目的目标是开发一些常用的图像分析应用程序并将其嵌入到Sedeen查看器中,为数字病理和癌症研究社区创建一个免费资源。到目前为止,已经开发了新的插件并将其纳入该平台,用于散焦检测、感兴趣区域转换和免疫组化切片分析。我们用MATLAB编写的生物标志物定量和细胞核分割算法也已集成到查看器中。本文介绍了该查看软件以及通过插件扩展功能的机制,并提供了简要描述作为示例,以指导想要使用该平台的用户。PIIP项目材料,包括描述其用法和应用的视频,以及Sedeen查看器、插件和用户手册的链接,可通过项目网页:http://pathiip.org免费获取。