2 citations · 4 across the 12 of their papers we have counts for
6 papers · 1 filter
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…
The Brain Resection Multimodal Image Registration (ReMIND2Reg) 2025 Challenge
Reuben Dorent, Laura Rigolo, Colin P. Galvin +8
Accurate intraoperative image guidance is critical for achieving maximal safe resection in brain tumor surgery, yet neuronavigation systems based on preoperative MRI lose accuracy…
Pretraining Deformable Image Registration Networks with Random Images
Junyu Chen, Shuwen Wei, Yihao Liu +2
Recent advances in deep learning-based medical image registration have shown that training deep neural networks~(DNNs) does not necessarily require medical images. Previous work sh…
Deep learning-derived arterial input function for dynamic brain PET
Junyu Chen, Zirui Jiang, Jennifer M. Coughlin +4
Dynamic positron emission tomography (PET) imaging combined with radiotracer kinetic modeling is a powerful technique for visualizing biological processes in the brain, offering va…
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…
Correlation Ratio for Unsupervised Learning of Multi-modal Deformable Registration
Xiaojian Chen, Yihao Liu, Shuwen Wei +3
In recent years, unsupervised learning for deformable image registration has been a major research focus. This approach involves training a registration network using pairs of movi…