Transforming medical imaging with Transformers? A comparative review of key properties, current progresses, and future perspectives

J Li, J Chen, Y Tang, C Wang, BA Landman… - Medical image …, 2023 - Elsevier
Transformer, one of the latest technological advances of deep learning, has gained
prevalence in natural language processing or computer vision. Since medical imaging bear …

Deep learning in medical image registration

X Chen, A Diaz-Pinto, N Ravikumar… - Progress in Biomedical …, 2021 - iopscience.iop.org
Image registration is a fundamental task in multiple medical image analysis applications.
With the advent of deep learning, there have been significant advances in algorithmic …

Large deformation diffeomorphic image registration with laplacian pyramid networks

TCW Mok, ACS Chung - … 2020: 23rd International Conference, Lima, Peru …, 2020 - Springer
Deep learning-based methods have recently demonstrated promising results in deformable
image registration for a wide range of medical image analysis tasks. However, existing deep …

Unsupervised 3D end-to-end medical image registration with volume tweening network

S Zhao, T Lau, J Luo, I Eric, C Chang… - IEEE journal of …, 2019 - ieeexplore.ieee.org
3D medical image registration is of great clinical importance. However, supervised learning
methods require a large amount of accurately annotated corresponding control points (or …

Shape-Former: Bridging CNN and Transformer via ShapeConv for multimodal image matching

J Chen, X Chen, S Chen, Y Liu, Y Rao, Y Yang… - Information …, 2023 - Elsevier
As with any data fusion task, the front-end of the pipeline for image fusion, aiming to collect
multitudinous physical properties from multimodal images taken by different types of …

Dual-stream pyramid registration network

M Kang, X Hu, W Huang, MR Scott, M Reyes - Medical image analysis, 2022 - Elsevier
We propose a Dual-stream Pyramid Registration Network (referred as Dual-PRNet) for
unsupervised 3D brain image registration. Unlike recent CNN-based registration …

U-net vs transformer: Is u-net outdated in medical image registration?

X Jia, J Bartlett, T Zhang, W Lu, Z Qiu… - International Workshop on …, 2022 - Springer
Due to their extreme long-range modeling capability, vision transformer-based networks
have become increasingly popular in deformable image registration. We believe, however …

Multi-modal bioelectrical signal fusion analysis based on different acquisition devices and scene settings: Overview, challenges, and novel orientation

J Li, Q Wang - Information Fusion, 2022 - Elsevier
Multi-modal fusion combines multiple modal information to overcome the limitation of
incomplete information expressed by a single modality, so as to realize the complementarity …

NonRegSRNet: A nonrigid registration hyperspectral super-resolution network

K Zheng, L Gao, D Hong, B Zhang… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Due to the limitations of imaging systems, satellite hyperspectral imagery (HSI), which yields
rich spectral information in many channels, often suffers from poor spatial resolution. HSI …

Anatomical invariance modeling and semantic alignment for self-supervised learning in 3d medical image analysis

Y Jiang, M Sun, H Guo, X Bai, K Yan… - Proceedings of the …, 2023 - openaccess.thecvf.com
Self-supervised learning (SSL) has recently achieved promising performance for 3D medical
image analysis tasks. Most current methods follow existing SSL paradigm originally …