An Image Analysis Resource for Cancer Research: PIIP—Pathology Image Informatics Platform for Visualization, Analysis, and Management
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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. Cancer Res; 77(21); e83–86. ©2017 AACR.
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- Authors
- Martel, A. L., Hosseinzadeh, D., Senaras, C., Zhou, Y., Yazdanpanah, A., Shojaii, R., Patterson, E. S., Madabhushi, A., & Gurcan, M. N.
- Affiliations
- University of Toronto (CA)
- 3Pathcore Inc., Toronto, Canada.
- 4The Ohio State University, Columbus, Ohio.
- Case Western Reserve University (US)
- Sunnybrook Research Institute (CA)
- The Ohio State University (US)
- Corresponding author
- Martel, Anne L.
- Venue
- Cancer Research
- Published
- 2017-10-31
- Volume
- 77
- Issue
- 21
- Pages
- e83-e86
- ISSN
- 0008-5472 (ISSN-L)
- 1538-7445
- PMC
- PMC5679396
- OpenAlex
- W2766877747
- Cited by
- 63
- References
- 12
- Citations by year
- 2026: 1 · 2025: 4 · 2024: 4 · 2023: 6 · 2022: 13 · 2021: 10 · 2020: 8 · 2019: 10 · 2018: 7
- FWCI
- 4.08
- Type
- journal article
- Language
- en
- Open access
- green
- europepmc.org
- Locations
- Cancer Research (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Cancer Institute (U24CA199374)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › AI in cancer detection
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Biophysics › Cell Image Analysis Techniques
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Radiomics and Machine Learning in Medical Imaging
- Keywords
- digital pathology, image analysis plugin, biomarker quantification, nuclei segmentation, cancer research resources
- MeSH terms
- Algorithms, Diagnostic Imaging, Humans, Image Interpretation, Computer-Assisted, Image Processing, Computer-Assisted, Neoplasms, Pathology, Clinical, Software, User-Computer Interface, Internet
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