ReviewMedical image analysis2025
A survey on deep learning in medical image registration: New technologies, uncertainty, evaluation metrics, and beyond.
Review in Medical image analysis, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 42 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
42 citing papers in PubMed.
- Robust cross-anatomy image registration leveraging keypoint priors and contour-based assessment.Medical & biological engineering & computing · 2026Article
- Comparative evaluation of VoxelMorpand conventional deformable image registration algorithms for thoracic 4D-CT in radiotherapy.Journal of applied clinical medical physics · 2026Article
- MSDW-Net: A Multi-Scale Network for Medical Image Registration Using Dynamic Wavelet Transform.Interdisciplinary sciences, computational life sciences · 2026Article
- Beyond the LUMIR challenge: The pathway to foundational registration models.Medical image analysis · 2026Article
- Attention-Guided TransMorph for Real-Time Tumor Tracking in Cine-MRI.Journal of imaging informatics in medicine · 2026Article
- Kinematic tracking of the small bones of the wrist in sequential 3DCT and dynamic 4DCT volume images using open-source Hierarchical 3D Registration, a module within SlicerAutoscoperBiomedical engineering online · 2026Article
- DSHARP: Deep Incompressible Motion Estimation With Sinusoidal-Transformed Harmonic Phase for Tagged MRI.IEEE transactions on medical imaging · 2026Article
- [A reweighted graph matching-based algorithm for automatic extraction of corresponding landmarks in medical images].Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi · 2026Article
- Pose-aware deep perceptual similarity for iterative 2D/3D registration of knee joints using contrastive learning.International journal of computer assisted radiology and surgery · 2026Article
- Review
- Fluoroscopy-Guided Motion Management in Particle Therapy: Evolution, Challenges, and AI-Enabled Opportunities.Tomography (Ann Arbor, Mich.) · 2026Review
- Can Artificial Intelligence Interpret Pulmonary Function Tests and Predict Prolonged Air Leaks After Lung Resection.Cancers · 2026Article
- Evaluation of classical and deep-learning deformable registration for magnetic resonance to four-dimensional computed tomography contour mapping in liver stereotactic body radiotherapy.Physics and imaging in radiation oncology · 2026Article
- Article
- An Effective Non-Rigid Registration Approach for Ultrasound Images Based on the Improved Variational Model of Intensity, Local Phase Information and Descriptor Matching.Journal of imaging · 2026Article
- Detection of Valve Vegetations in Native and Prosthetic Valves using Echocardiographic Radiomics and Deep Learning on Transesophageal Echocardiography Images.Journal of biomedical physics & engineering · 2026Article
- Robust registration under large image misalignment using an iterative step-aware transformer with application to corneal confocal microscopy.Biomedical optics express · 2026Article
- Unsupervised learning of spatially varying regularization for diffeomorphic image registration.Medical image analysis · 2026Article
- On the degrees of freedom of gridded control points in learning-based medical image registration.Medical physics · 2026Article
- Insertion Network for Image Sequence Correspondence Building.Proceedings of SPIE--the International Society for Optical Engineering · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
Abstract
Deep learning technologies have dramatically reshaped the field of medical image registration over the past decade. The initial developments, such as regression-based and U-Net-based networks, established the foundation for deep learning in image registration. Subsequent progress has been made in various aspects of deep learning-based registration, including similarity measures, deformation regularizations, network architectures, and uncertainty estimation. These advancements have not only enriched the field of image registration but have also facilitated its application in a wide range of tasks, including atlas construction, multi-atlas segmentation, motion estimation, and 2D-3D registration. In this paper, we present a comprehensive overview of the most recent advancements in deep learning-based image registration. We begin with a concise introduction to the core concepts of deep learning-based image registration. Then, we delve into innovative network architectures, loss functions specific to registration, and methods for estimating registration uncertainty. Additionally, this paper explores appropriate evaluation metrics for assessing the performance of deep learning models in registration tasks. Finally, we highlight the practical applications of these novel techniques in medical imaging and discuss the future prospects of deep learning-based image registration.
Indexed as
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What Socratic holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.