The CRS4 Digital Pathology Platform (CDPP) is a web-based system for the interactive visualization and structured annotation of Whole Slide Images (WSIs) in digital and computational pathology research. Designed to facilitate the development of high-quality interoperable datasets, CDPP integrates OMERO for image management and visualization with custom modules for annotation and model integration, including support for deploying deep learning models for tissue classification and region detection.
The development of the platform began through collaboration between CRS4 and the Karolinska Institutet as part of the ProMort project, a multi-disciplinary and international research initiative aiming to develop advanced prognostic tools for prostate cancer that support personalized treatment decisions. Within this context, CDPP enabled large-scale review and annotation of prostate tissue images.
The platform's capabilities were further extended through the DeepHealth project, where artificial intelligence techniques were integrated to support automated detection and classification of tumor regions in digital slides.
In addition, CDPP is actively used in the Turin Prostate Cancer Prognostication (TPCP) study, an observational cohort study initiated in 2021 by the Department of Medical Sciences at the University of Turin, and funded by the AIRC Foundation for Cancer Research. The study seeks to build a novel, integrated prognostic model for prostate cancer.
Comprehensive documentation for installation and usage is available on our GitHub Pages site.
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Del Rio, M., et al. (2022). AI support for accelerating histopathological slide examinations of prostate cancer in clinical studies. In: International Conference on Image Analysis and Processing. Springer, Cham.
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Zelic, R., et al. (2019). Estimation of relative and absolute risks in a competing-risks setting using a nested case-control study design: example from the ProMort study. American Journal of Epidemiology, 188(6), 1165-1173.
