Challenge Outcomes 🏁


Open-Source AI Algorithms 👩‍💻👨‍💻

Through the PI-CAI challenge, as a community, we have conceived and validated the following baseline and state-of-the-art AI algorithms for clinically significant prostate cancer diagnosis in MRI. We encourage everyone to use and adopt these resources as the starting point for developing new ideas and their very own prostate-AI solutions for cancer management. 
🚧 Access to the following trained GC algorithms will be made open to everyone, pending publication of the PI-CAI challenge outcomes in a journal paper tentatively in Fall 2023.

# Algorithm Inference Algorithm (Closed Testing Phase) Inference Algorithm (Open Development Phase) Training Code Inference Code
1

DataScientX (N. Debs, A. Routier, et al.; France) 

Grand Challenge Grand Challenge N/A N/A
2

BDAV_Y (Y. Yuan, et al.; Australia)

Grand Challenge Grand Challenge Pending Pending
3

Swangeese (H. Kan, et al.; China)

Grand Challenge Grand Challenge GitHub GitHub
4

PIMed-Stanford (X. Li, S. Vesal, S. Saunders, et al.; USA)

Grand Challenge Grand Challenge N/A N/A
5

HeviAI (A. Karagoz, et al.; Turkey)

Grand Challenge Grand Challenge Pending
Pending
6 nnDetection (supervised) Grand Challenge Grand Challenge GitHub GitHub
7 nnU-Net (semi-supervised) Grand Challenge Grand Challenge GitHub GitHub
8 nnDetection (semi-supervised) Grand Challenge Grand Challenge GitHub GitHub
9 nnU-Net (supervised) Grand Challenge Grand Challenge GitHub GitHub
10 U-Net (semi-supervised) Grand Challenge Grand Challenge GitHub GitHub
11 U-Net (supervised) Grand Challenge Grand Challenge GitHub GitHub

Stay tuned for more updates on this page!