ArticleMedical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention2024
uniGradICON: A Foundation Model for Medical Image Registration.
Article in Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 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
17 citing papers in PubMed.
- AI-driven ablative margin assessment after HCC radiofrequency ablation: a case-control feasibility study.European radiology experimental · 2026Article
- Beyond the LUMIR challenge: The pathway to foundational registration models.Medical image analysis · 2026Article
- A method for tissue-mask supported whole-body image registration in the UK Biobank.Scientific reports · 2026Article
- Adaptive Riemannian optimization for multi-scale diffeomorphic matching.Nature communications · 2026Article
- CoRe: Joint Optimization with Contrastive Learning for Medical Image Registration.Sensors (Basel, Switzerland) · 2026Article
- Vision foundation model for 3D magnetic resonance imaging segmentation, classification, and registration.Medical image analysis · 2026Article
- On the accuracy of image registration in portable low-field 3D brain MRI.Research square · 2026Article
- On the accuracy of image registration in portable low-field 3D brain MRI.bioRxiv : the preprint server for biology · 2026Article
- Unsupervised learning of spatially varying regularization for diffeomorphic image registration.Medical image analysis · 2026Article
- Unified Brain Surface and Volume Registration.... International Conference on Learning Representations · 2026Article
- Foundation Models Meet Medical Image Interpretation.Research (Washington, D.C.) · 2026Review
- A survey of transformer-based architectures in medical image analysis: models, applications, and challenges.Frontiers in artificial intelligence · 2026Review
- PolyPose: Deformable 2D/3D Registration via Polyrigid Transformations.Advances in neural information processing systems · 2025Article
- Article
- CARL: A Framework for Equivariant Image Registration.Proceedings. IEEE Computer Society Conference on Computer Vision and Pattern Recognition · 2025Article
- Learning General-Purpose Biomedical Volume Representations using Randomized Synthesis.... International Conference on Learning Representations · 2025Article
- Comprehensive Review: Machine and Deep Learning in Brain Stroke Diagnosis.Sensors (Basel, Switzerland) · 2024Review
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
Conventional medical image registration approaches directly optimize over the parameters of a transformation model. These approaches have been highly successful and are used generically for registrations of different anatomical regions. Recent deep registration networks are incredibly fast and accurate but are only trained for specific tasks. Hence, they are no longer generic registration approaches. We therefore propose uniGradICON, a first step toward a foundation model for registration providing 1) great performance
Indexed as
Identifiers
What OpenQuestion 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 OpenQuestion graph.