4 citations · 4 across the 6 of their papers we have counts for
7 papers
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…
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…
A Narrative Review of Image Processing Techniques Related to Prostate Ultrasound
Haiqiao Wang, Hong Wu, Zhuoyuan Wang +4
Prostate cancer (PCa) poses a significant threat to men's health, with early diagnosis being crucial for improving prognosis and reducing mortality rates. Transrectal ultrasound (T…
Encoding Matching Criteria for Cross-domain Deformable Image Registration
Zhuoyuan Wang, Haiqiao Wang, Yi Wang
Most existing deep learning-based registration methods are trained on single-type images to address same-domain tasks.However, cross-domain deformable registration remains challeng…
Contextual Embedding Learning to Enhance 2D Networks for Volumetric Image Segmentation
Zhuoyuan Wang, Dong Sun, Xiangyun Zeng +2
The segmentation of organs in volumetric medical images plays an important role in computer-aided diagnosis and treatment/surgery planning. Conventional 2D convolutional neural net…
ModeTv2: GPU-accelerated Motion Decomposition Transformer for Pairwise Optimization in Medical Image Registration
Haiqiao Wang, Zhuoyuan Wang, Dong Ni +1
Deformable image registration plays a crucial role in medical imaging, aiding in disease diagnosis and image-guided interventions. Traditional iterative methods are slow, while dee…
Pyramid Attention Network for Medical Image Registration
Zhuoyuan Wang, Haiqiao Wang, Yi Wang
The advent of deep-learning-based registration networks has addressed the time-consuming challenge in traditional iterative methods.However, the potential of current registration n…