ReviewPhysics in medicine and biology2020
Deep learning in medical image registration: a review.
Review in Physics in medicine and biology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 196 papers, 4 of them syntheses that pooled it.
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
196 citing papers in PubMed, 4 syntheses or guidelines pooled it.
- Towards more precise automatic analysis: a systematic review of deep learning-based multi-organ segmentation.Biomedical engineering online · 2024Pooled it
- Deep learning in MRI-guided radiation therapy: A systematic review.Journal of applied clinical medical physics · 2024Pooled it
- A systematic review of automated methods to perform white matter tract segmentation.Frontiers in neuroscience · 2024Pooled it
- Current Status of Objectification of Four Diagnostic Methods on Constitution Recognition of Chinese Medicine.Chinese journal of integrative medicine · 2022Pooled it
- Contrast-enhanced harmonic endoscopic ultrasound (CH-EUS) MASTER: A novel deep learning-based system in pancreatic mass diagnosis.Cancer medicine · 2023Trial
- Automated quality assurance of rigid brain CT/MR image registration using a 3D convolutional neural network.Journal of applied clinical medical physics · 2026Article
- Three-dimensional image metric maps for characterizing local image changes associated with AI-based motion correction in coronary CT.Radiological physics and technology · 2026Article
- VITAL: Value-Invariant Transformation and Alignment Learning for quantitative photoacoustic microscopy.Photoacoustics · 2026Article
- Beyond CT: Attenuation correction for stand-alone brain PET.Zeitschrift fur medizinische Physik · 2026Review
- Development and evaluation of an automated report-based chart checking tool in external beam radiotherapy.Journal of applied clinical medical physics · 2026Article
- CRR-Net: a correlation reconstruction and refinement network for deformable medical image registration.Visual computing for industry, biomedicine, and art · 2026Article
- Deep learning-driven inversion framework for shear modulus estimation in magnetic resonance elastography.Magma (New York, N.Y.) · 2026Article
- Progress of Multimodal Imaging: Bridging Orthodontics to Comprehensive Oral Multidisciplinary Care.International dental journal · 2026Review
- Review
- Fluoroscopy-Guided Motion Management in Particle Therapy: Evolution, Challenges, and AI-Enabled Opportunities.Tomography (Ann Arbor, Mich.) · 2026Review
- On the accuracy of image registration in portable low-field 3D brain MRI.Research square · 2026Article
- Quantifying the Efficacy of Deep Learning-Driven Deformable Registration in Multiplexed-Immunofluorescence Imaging for Nucleus Subtype Classification.The journal of machine learning for biomedical imaging · 2026Article
- An effective deep learning algorithm for medical image registration.PLOS digital health · 2026Article
- PET Head Motion Estimation Using Supervised Deep Learning With Attention.IEEE transactions on medical imaging · 2026Article
- On the accuracy of image registration in portable low-field 3D brain MRI.bioRxiv : the preprint server for biology · 2026Article
136 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
This paper presents a review of deep learning (DL)-based medical image registration methods. We summarized the latest developments and applications of DL-based registration methods in the medical field. These methods were classified into seven categories according to their methods, functions and popularity. A detailed review of each category was presented, highlighting important contributions and identifying specific challenges. A short assessment was presented following the detailed review of each category to summarize its achievements and future potential. We provided a comprehensive comparison among DL-based methods for lung and brain registration using benchmark datasets. Lastly, we analyzed the statistics of all the cited works from various aspects, revealing the popularity and future trend of DL-based medical image registration.
Indexed as
Identifiers
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.