collaborators

13 papers

eess.IV2026

Beyond the LUMIR challenge: The pathway to foundational registration models

Junyu Chen, Shuwen Wei, Joel Honkamaa +33

Medical image challenges have played a transformative role in advancing the field, catalyzing innovation and establishing new performance benchmarks. Image registration, a foundati…

cs.CV2026

Unsupervised MR-US Multimodal Image Registration with Multilevel Correlation Pyramidal Optimization

Jiazheng Wang, Zeyu Liu, Min Liu +4

Surgical navigation based on multimodal image registration has played a significant role in providing intraoperative guidance to surgeons by showing the relative position of the ta…

cs.CV2026

FMIR, a foundation model-based Image Registration Framework for Robust Image Registration

Fengting Zhang, Yue He, Qinghao Liu +3

Deep learning has revolutionized medical image registration by achieving unprecedented speeds, yet its clinical application is hindered by a limited ability to generalize beyond th…

cs.CV2026

Encoder-Only Image Registration

Xiang Chen, Renjiu Hu, Jinwei Zhang +5

Learning-based techniques have significantly improved the accuracy and speed of deformable image registration. However, challenges such as reducing computational complexity and han…

eess.IV2026

Learn2Reg 2024: New Benchmark Datasets Driving Progress on New Challenges

Lasse Hansen, Wiebke Heyer, Christoph Großbröhmer +51

Medical image registration is critical for clinical applications, and fair benchmarking of different methods is essential for monitoring ongoing progress in the field. To date, the…

eess.IV2025

MSRepaint: Multiple Sclerosis Repaint with Conditional Denoising Diffusion Implicit Model for Bidirectional Lesion Filling and Synthesis

Jinwei Zhang, Lianrui Zuo, Yihao Liu +10

In multiple sclerosis, lesions interfere with automated magnetic resonance imaging analyses such as brain parcellation and deformable registration, while lesion segmentation models…