Dataset Open Access
The PI-CAI Challenge: Public Training and Development Dataset
Saha, Anindo;
Twilt, Jasper Jonathan;
Bosma, Joeran Sander;
van Ginneken, Bram;
Yakar, Derya;
Elschot, Mattijs;
Veltman, Jeroen;
Fütterer, Jurgen;
de Rooij, Maarten;
Huisman, Henkjan
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).
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md5:bd06674082883348303979bec15d9c2c |
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picai_public_images_fold0.zip
md5:b0cdd8f5fb7733ca585dca3541586a34 |
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picai_public_images_fold1.zip
md5:d7c8cd0efc0e7f264df8d5acf860662f |
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picai_public_images_fold2.zip
md5:5ac0caf27cfe94dfc04bb408a971b351 |
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picai_public_images_fold3.zip
md5:6602bce3d0882d7b9c2153d880c97e96 |
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picai_public_images_fold4.zip
md5:8941720d8a8ee66571691cfb10dbee66 |
5.6 GB | Download |
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README.md
md5:3ef8691b42259a6b908c85b68d00e114 |
4.3 kB | Download |
| All versions | This version | |
|---|---|---|
| Views | 6,164 | 4,087 |
| Downloads | 12,256 | 9,421 |
| Data volume | 61.4 TB | 45.7 TB |
| Unique views | 4,925 | 3,366 |
| Unique downloads | 4,117 | 3,077 |
- Publication date:
- June 10, 2022
- DOI:
-
- Keyword(s):
- prostate cancer artificial intelligence magnetic resonance imaging radiologists computer-aided detection and diagnosis
- Grants:
-
European Commission:
- ProCAncer-I - An AI Platform integrating imaging data and models, supporting precision care through prostate cancer’s continuum (952159)
- Related identifiers:
- Documented by
- 10.5281/zenodo.6522364 (Report)
- Communities:
- License (for files):
- Creative Commons Attribution Non Commercial 4.0 International