Registration Algorithms
Participants submit deformable displacement field algorithms to align medical image pairs for evaluation on clinical benchmarks.
AI/CORE Unranked
L2R 2026
Learn2Reg 2026
Learn2Reg 2026 is a medical image registration challenge hosted at MICCAI 2026 in Strasbourg, focusing on clinically relevant benchmarks for deformable image registration. It features two tasks—PSMAReg for longitudinal PSMA PET/CT scans and Learn2Breath for inspiratory-expiratory chest CT scans—partnering with SNMMI and COPDGene to promote robust, quantifiable, and clinically applicable registration methods.
Paper fit
Contribution paths
A strong submission should clearly identify its contribution and evaluate it appropriately.
Research areas in scope
01
Challenge Tasks
PSMAReg: registration of pre-therapy and follow-up whole-body PSMA PET/CT scansLearn2Breath: registration of inspiratory and expiratory chest CT scans
Policies worth checking twice
- Evaluation is conducted using Docker containers on GPUs provided by organizers
- Submission must include code for deformable displacement fields
- Evaluation metrics include Dice/surface distance, TRE, Jacobian determinant, and computation time
- Anatomical segmentation labels, manual landmarks, masks, and keypoint correspondences are provided for training and evaluation
Official sources
Compiled from the official call for papers. The organizers’ pages remain authoritative.
Last verified September 9, 2026