American Association for Cancer Research
00085472can170323-sup-178380_2_supp_4104388_9rl99v.pdf (742.49 kB)

Quantitative comparison of IHC staining from An Image Analysis Resource for Cancer Research: PIIP—Pathology Image Informatics Platform for Visualization, Analysis, and Management

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journal contribution
posted on 2023-03-31, 01:41 authored by Anne L. Martel, Dan Hosseinzadeh, Caglar Senaras, Yu Zhou, Azadeh Yazdanpanah, Rushin Shojaii, Emily S. Patterson, Anant Madabhushi, Metin N. Gurcan

Description of a use case to illistrate workflow with Sedeen Viewer


National Cancer Institute



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: Cancer Res; 77(21); e83–86. ©2017 AACR.

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