Unsupervised Learning of Diffeomorphic Image Registration via TransMorph

We propose a learning-based framework for unsupervised and end-to-end learning of diffeomorphic image registration. Specifically, the proposed network learns to produce and integrate time-dependent velocity fields in an LDDMM setting.

This repository contains the source code for two models, TM-TVF_LDDMM and TM-TVF, from our paper: "Unsupervised Learning of Diffeomorphic Image Registration via TransMorph"

• Paper link: Chen, Junyu, Eric C. Frey, and Yong Du. "Unsupervised Learning of Diffeomorphic Image Registration via TransMorph." International Workshop on Biomedical Image Registration. Springer, Cham, 2022.
• This method is currently ranked No. 1 @ 2021 MICCAI Learn2Reg challenge Task 03 (OASIS brain MR dataset)
• Please also check out our base network, TransMorph, a top-ranked Transformer-based network for image registration.
• Preprocessed datasets were made available @ TransMorph

Modeling time-dependent velocity fields using TransMorph:

Skip-connections were omitted for visualization.

Smoother transformation without imposing a diffeomorphism:

Diffeomorphic registration

Forward:
 

Inverse:
 

Inversion and composition:

State-of-the-art performance:

Click on the Model Weights to start downloading the pre-trained weights.
We also provided the Tensorboard training log for each model. To visualize loss and validation curves, run:
Tensorboard --logdir=*training log file name* in terminal. Note: This requires Tensorboard installation (pip install tensorboard).

2021 MICCAI Learn2Reg challenge Task 03:

Validation set results

Ranking	Model	Dice	SDlogJ	HdDist95
1	TM-TVF	0.8706 ± 0.0154	0.0998	1.3903
2	TM-Large	0.8623 ± 0.0144	0.1276	1.4315
3	TransMorph (TM)	0.8575 ± 0.0145	0.1253	1.4594
4	TransMorph-TVF_LDDMM	0.833 ± 0.016	0.090	1.630

Test set results (results obtained from Learn2Reg challenge organizers)

Ranking	Model	Dice	SDlogJ	HdDist95
1	TM-TVF	0.8241 ± 0.1516	0.0905 ± 0.0054	1.6329 ± 0.4358
2	TM-Large	0.8196 ± 0.1497	0.1244 ± 0.0148	1.6564 ± 1.7368
3	TM	0.8162 ± 0.1541	0.1242 ± 0.0136	1.6920 ± 1.7587
4	LapIRN	0.82	0.07	1.67
5	ConvexAdam	0.81	0.07	1.63
...