The PI-CAI Challenge: Public Training and Development Dataset
Creators
- 1. Department of Medical Imaging, Radboud University Medical Center, The Netherlands
- 2. Department of Radiology, Nuclear Medicine and Molecular Imaging, University Medical Center Groningen, The Netherlands
- 3. Department of Circulation and Medical Imaging, Norwegian University of Science and Technology, Norway
- 4. Department of Radiology, Ziekenhuis Groep Twente, The Netherlands
Description
This dataset represents the PI-CAI: Public Training and Development Dataset. It contains 1500 anonymized prostate biparametric MRI scans from 1476 patients, acquired between 2012-2021, at three centers (Radboud University Medical Center, University Medical Center Groningen, Ziekenhuis Groep Twente) based in The Netherlands.
The PI-CAI challenge is an all-new grand challenge that aims to validate the diagnostic performance of artificial intelligence and radiologists at clinically significant prostate cancer (csPCa) detection/diagnosis in MRI, with histopathology and follow-up (≥ 3 years) as the reference standard, in a retrospective setting. The study hypothesizes that state-of-the-art AI algorithms, trained using thousands of patient exams, are non-inferior to radiologists reading bpMRI.
Key aspects of the PI-CAI study design have been established in conjunction with an international scientific advisory board of 16 experts in prostate AI, radiology and urology —to unify and standardize present-day guidelines, and to ensure meaningful validation of prostate AI towards clinical translation (Reinke et al., 2021).
Files
picai_public_images_fold0.zip
Files
(32.5 GB)
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Additional details
Related works
- Is documented by
- Report: 10.5281/zenodo.6522364 (DOI)