Recursive deformable pyramid network for unsupervised medical image registration

H Wang, D Ni, Y Wang - IEEE Transactions on Medical Imaging, 2024 - ieeexplore.ieee.org
Complicated deformation problems are frequently encountered in medical image
registration tasks. Although various advanced registration models have been proposed …

Non-iterative coarse-to-fine transformer networks for joint affine and deformable image registration

M Meng, L Bi, M Fulham, D Feng, J Kim - International Conference on …, 2023 - Springer
Image registration is a fundamental requirement for medical image analysis. Deep
registration methods based on deep learning have been widely recognized for their …

Progressive feedback residual attention network for cardiac magnetic resonance imaging super-resolution

D Qiu, Y Cheng, X Wang - IEEE Journal of Biomedical and …, 2023 - ieeexplore.ieee.org
Atrial fibrillation (AF) is an increasing medical burden worldwide, and its pathological
manifestations are atrial tissue remodeling and low-pressure atrial tissue fibrosis. Due to the …

Self-distilled hierarchical network for unsupervised deformable image registration

S Zhou, B Hu, Z ** network with contextual fusion
Z Tan, L Zhang, Y Lv, Y Ma, H Lu - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Pyramid-based deformation decomposition is a promising registration framework, which
gradually decomposes the deformation field into multi-resolution subfields for precise …

ModeTv2: GPU-accelerated motion decomposition transformer for pairwise optimization in medical image registration

H Wang, Z Wang, D Ni, Y Wang - arxiv preprint arxiv:2403.16526, 2024 - arxiv.org
Deformable image registration plays a crucial role in medical imaging, aiding in disease
diagnosis and image-guided interventions. Traditional iterative methods are slow, while …

HGCMorph: joint discontinuity-preserving and pose-learning via GNN and capsule networks for deformable medical images registration

Z Yan, J Ji, J Ma, W Cao - Physics in Medicine & Biology, 2024 - iopscience.iop.org
Objective. This study aims to enhance medical image registration by addressing the
limitations of existing approaches that rely on spatial transformations through U-Net …