Learn2Reg Repository

Repository for additional L2R files

Including:

• evaluation files
• a list of publicly available registration tools
• utilities (soon)

What is Learn2Reg?

Learn2Reg is a comprehensive multi-task medical image registration challenge, hosted on https://learn2reg.grand-challenge.org/. Have a look!

Are you looking to benchmark your registration algorithm? Please visit https://learn2reg-test.grand-challenge.org/, where you can evaluate your algorithm on data from former Learn2Reg-challenges.

Motivation: Standardised benchmark for the best conventional and learning based medical registration methods:

• Analyse accuracy, robustness and speed on complementary tasks for clinical impact.
• Remove entry barriers for new teams with expertise in deep learning but not necessarily registration.

Learn2Reg removes pitfalls for learning and applying transformations by providing:

• python evaluation code for voxel displacement fields and open-source code all evaluation metrics
• anatomical segmentation labels, manual landmarks, masks and keypoint correspondences for deep learning

Learn2Reg addresses four of the imminent challenges of medical image registration:

• learning from relatively small datasets
• estimating large deformations
• dealing with multi-modal scans
• learning from noisy annotations

Evaluation: Comprehensive and fair evaluation criteria that include:

• Dice / surface distance and TRE toe measure accuracy and robustness of transferring anatomical annotations
• standard deviation and extreme values of Jacobian determinant to promote plausible deformations,
• low computation time for easier clinical translation evaluated using docker containers on GPUs provided by organisers.

Any questions? Head to our forum at https://learn2reg.grand-challenge.org/ or mail us directly via learn2reg@gmail.com.

Public methods of L2R partipants / baselines (alphabetical order)

• Bailiang https://github.com/BailiangJ/learn2reg2021_task3
• ConvexAdam 🥇 🥇 🥈 🥈 🥉 🥉 https://github.com/multimodallearning/convexAdam
• CorrField 🥇 🥇 🥈 https://grand-challenge.org/algorithms/corrfield/
• Estienne 🥉 https://github.com/TheoEst/abdominal_registration
• Gunnarson https://github.com/ngunnar/learning-a-deformable-registration-pyramid
• Imperial https://github.com/biomedia-mira/istn
• LapIRN 🥇 🥇 🥈 🥉 https://github.com/cwmok/Conditional_LapIRN
• Multi-brain https://github.com/WTCN-computational-anatomy-group/mb
• Nifty-Reg https://github.com/KCL-BMEIS/niftyreg
• PDD-Net 🥈 https://github.com/multimodallearning/pdd_net
• Winter https://github.com/WinterPan2017/ADLReg