ODELIA Pimed Model

Three-class 3D breast MRI classification model contributed by the Pimed team to the ODELIA Challenge 2025.

The source repository is dnschouten/odelia_submission_pimed.

Method

The corresponding implementation in the ODELIA project uses a 3D ResNet-18 backbone with one input channel and three output classes. It wraps the model for subject-level classification of ODELIA MRI volumes.

The exact preprocessing, checkpoint configuration, and evaluation procedure must be taken from the authors' source repository and the files uploaded with this model. Do not infer clinical performance from the architecture alone.

Intended use and limitations

This release is for research and benchmarking only. It is not a medical device, is not clinically validated, and must not be used for diagnosis, prognosis, treatment, triage, or other clinical decisions. Performance may vary across institutions, scanners, acquisition protocols, and populations.

Setup

Use the source repository for the authoritative setup and inference commands:

git clone https://github.com/dnschouten/odelia_submission_pimed.git
cd odelia_submission_pimed

License and attribution

The implementation uses PyTorch/MONAI components. Their applicable licenses, notices, and any pretrained-weight terms must be preserved and reviewed before redistribution.

Please cite or acknowledge:

• ODELIA Challenge 2025 and the ODELIA consortium.
• The Pimed authors: Daan Schouten, Jeong Hoon Lee, Mirabela Rusu and source repository.
• The ODELIA paper: arXiv:2506.00474.

For questions regarding model architecture, training, or permissions, please contact Daan Schouten.