A survey on deep learning in medical image registration: new technologies, uncertainty, evaluation metrics, and beyond

This official repository contains a comprehensive list of papers on learning-based image registration. Additionally, it includes Python implementations of various image similarity measures, deformation regularization techniques, and evaluation methods for medical image registration.

$${\color{red}New!}$$ 10/04/2024 - Our paper has been accepted by Medical Image Analysis for publication! [Link]

Overview

• Citation
• Loss functions for image registration
  • Image similarity measures
  • Deformation regularization
• Network architectures
  • Conventional ConvNets
  • Adversarial learning
  • Contrastive learning
  • Transformers
  • Diffusion models
  • Neural ODEs
  • Implicit neural representations
  • Hyperparameter conditioning
  • Anatomy-aware networks
  • Correlation layer
  • Progressive and pyramid registration
• Registration uncertainty
• Benchmark dataset for medical image registration
• Applications of image registration
  • Atlas construction
  • Multi-atlas segmentation
  • Uncertainty
  • Motion estimation
  • 2D-3D registration
• Towards Zero-shot Registration (Fundation Models)
• Trends in image registration-related research based on PubMed paper counts

Citation

These Python implementations and the list of papers have been prepared for inclusion in the following article:

@article{chen2023survey,
title = {A survey on deep learning in medical image registration: New technologies, uncertainty, evaluation metrics, and beyond},
author = {Junyu Chen and Yihao Liu and Shuwen Wei and Zhangxing Bian and Shalini Subramanian and Aaron Carass and Jerry L. Prince and Yong Du},
journal = {Medical Image Analysis},
pages = {103385},
year = {2024},
issn = {1361-8415},
doi = {https://doi.org/10.1016/j.media.2024.103385}
}

Loss Functions

Image similarity measures

• Mean Squared Error (MSE)
• Mean Absolute Error (MAE)
• Pearson's correlation (PCC) [Code]
• Local normalized cross-correlation (LNCC) based on square window [Code]
• Local normalized cross-correlation (LNCC) based on Gaussian window [Code]
• Modality independent neighbourhood descriptor (MIND) [Code]
• Mutual Information (MI) [Code]
• Local mutual information (LMI) [Code]
• Structural Similarity Index (SSIM) [Code]
• Normalized Gradient Fields (NGF) [GitHub]
• $${\color{red}New!}$$ Correlation Ratio (CR) [Code][Paper]
• $${\color{red}New!}$$ Local correlation ratio [Code][Paper]

Deformation regularization

• Diffusion regularization [Code, use penalty='l2']
• Total-Variation regularization [Code, use penalty='l1']
• Isotropic Total-Variation regularization [Code]
• Bending energy [Code]
• ICON
  • "ICON: Learning Regular Maps Through Inverse Consistency", ICCV, 2021 (Greer et al.). [Paper][GitHub]
• GradICON
  • "GradICON: Approximate Diffeomorphisms via Gradient Inverse Consistency", CVPR, 2022 (Tian et al.). [Paper][GitHub]
• Inverse consistency by construction
  • "Inverse consistency by construction for multistep deep registration", MICCAI, 2023 (Greer et al.). [Paper][GitHub]
• $${\color{red}New!}$$ Spatially varying regularization
  • "Unsupervised learning of spatially varying regularization for diffeomorphic image registration", arXiv, 2023 (Chen et al.). [Paper][GitHub]

Network Architectures

Conventional ConvNets

• "Nonrigid image registration using multi-scale 3D convolutional neural networks", MICCAI, 2017 (Sokooti et al.). [Paper][GitHub]
• "End-to-end unsupervised deformable image registration with a convolutional neural network", DLMIA, 2017 (De Vos et al.). [Paper][GitHub]
• "Quicksilver: Fast predictive image registration–a deep learning approach", NeuroImage, 2017 (Yang et al.). [Paper][GitHub]
• "Voxelmorph: a learning framework for deformable medical image registration", IEEE TMI, 2017 (Balakrishnan et al.). [Paper][GitHub]
• "Unsupervised learning of probabilistic diffeomorphic registration for images and surfaces", MedIA, 2019 (Dalca et al.). [Paper][GitHub]
• "Deepflash: An efficient network for learning-based medical image registration", CVPR, 2020 (Wang et al.). [Paper][GitHub]
• "CycleMorph: cycle consistent unsupervised deformable image registration", MedIA, 2021 (Kim et al.). [Paper][GitHub]
• "U-net vs transformer: Is u-net outdated in medical image registration?", MLMI, 2022 (Jia et al.). [Paper][GitHub]

Adversarial learning

• "Adversarial similarity network for evaluating image alignment in deep learning based registration", MICCAI, 2018 (Fan et al.). [Paper]
• "Adversarial image registration with application for MR and TRUS image fusion", MLMI, 2018 (Yan et al.). [Paper]
• "Deformable medical image registration using generative adversarial networks", ISBI, 2018 (Mahapatra et al.). [Paper]
• "Joint registration and segmentation of xray images using generative adversarial networks", MLMI, 2018 (Mahapatra et al.). [Paper]
• "Training data independent image registration using generative adversarial networks and domain adaptation", PR, 2020 (Mahapatra et al.). [Paper]
• "Unsupervised deformable registration for multi-modal images via disentangled representations", IPMI, 2019 (Qin et al.). [Paper]
• "Adversarial optimization for joint registration and segmentation in prostate CT radiotherapy", MICCAI, 2019 (Elmahdy et al.). [Paper]
• "Adversarial learning for deformable registration of brain MR image using a multi-scale fully convolutional network", BSPC, 2019 (Duan et al.). [Paper]
• "Adversarial learning for deformable image registration: Application to 3D ultrasound image fusion", SUSI&PIPPI, 2019 (Li and Ogino). [Paper]
• "Deformable adversarial registration network with multiple loss constraints", CMIG, 2019 (Luo et al.). [Paper]
• "Adversarial learning for mono-or multi-modal registration", MedIA, 2019 (Fan et al.). [Paper]
• "Adversarial uni-and multi-modal stream networks for multimodal image registration", MICCAI, 2020 (Xu et al.). [Paper]
• "Synthesis and inpainting-based MR-CT registration for image-guided thermal ablation of liver tumors", MICCAI, 2019 (Wei et al.). [Paper]
• "SymReg-GAN: symmetric image registration with generative adversarial networks", IEEE TPAMI, 2021 (Zheng et al.). [Paper]
• "Deformable MR-CT image registration using an unsupervised, dual-channel network for neurosurgical guidance", MedIA, 2022 (Han et al.). [Paper]
• "United multi-task learning for abdominal contrast-enhanced CT synthesis through joint deformable registration", CMPB, 2023 (Zhong et al.). [Paper]
• "Light-weight deformable registration using adversarial learning with distilling knowledge", IEEE TMI, 2022 (Tran et al.). [Paper][GitHub]

Contrastive learning

• "Towards accurate and robust multi-modal medical image registration using contrastive metric learning", IEEE Access, 2019 (Hu et al.). [Paper]
• "CoMIR: Contrastive multimodal image representation for registration", NeurIPS, 2020 (Pielawski et al.). [Paper][GitHub]
• "Can representation learning for multimodal image registration be improved by supervision of intermediate layers?", ICPRIA, 2023 (Wetzer et al.). [Paper]
• "Synth-by-reg (sbr): Contrastive learning for synthesis-based registration of paired images", SASHIMI, 2021 (Casamitjana et al.). [Paper][GitHub]
• "ContraReg: Contrastive Learning of Multi-modality Unsupervised Deformable Image Registration", MICCAI, 2022 (Dey et al.). [Paper][GitHub]
• "Contrastive registration for unsupervised medical image segmentation", IEEE TNNLS, 2023 (Liu et al.). [Paper]
• "PC-SwinMorph: Patch representation for unsupervised medical image registration and segmentation", ArXiv, 2022 (Liu et al.). [Paper]

Transformers

• "ViT-V-Net: Vision Transformer for Unsupervised Volumetric Medical Image Registration", MIDL, 2021 (Chen et al.). [Paper][GitHub]
• "Transmorph: Transformer for unsupervised medical image registration", MedIA, 2022 (Qin et al.). [Paper][GitHub]
• "Learning dual transformer network for diffeomorphic registration", MICCAI, 2021 (Zhang et al.). [Paper]
• "Affine Medical Image Registration with Coarse-to-Fine Vision Transformer", CVPR, 2022 (Mok et al.). [Paper][GitHub]
• "Deformer: Towards displacement field learning for unsupervised medical image registration", MICCAI, 2022 (Chen et al.). [Paper][GitHub]
• "PC-Reg: A pyramidal prediction--correction approach for large deformation image registration", MedIA, 2023 (Yin et al.). [Paper]
• "Cross-modal attention for multi-modal image registration", MedIA, 2022 (Song et al.). [Paper][GitHub]
• "Xmorpher: Full transformer for deformable medical image registration via cross attention", MICCAI, 2022 (Shi et al.). [Paper][GitHub]
• "Deformable cross-attention transformer for medical image registration", MLMI, 2023 (Chen et al.). [Paper][GitHub]
• "TransMatch: a transformer-based multilevel dual-stream feature matching network for unsupervised deformable image registration", IEEE TMI, 2023 (Chen et al.). [Paper][GitHub]
• "Coordinate translator for learning deformable medical image registration", MMMI, 2022 (Liu et al.). [Paper]
• "ModeT: Learning Deformable Image Registration via Motion Decomposition Transformer", MICCAI, 2023 (Wang et al.). [Paper][GitHub]
• "Anatomically constrained and attention-guided deep feature fusion for joint segmentation and deformable medical image registration", MedIA, 2023 (Khor et al.). [Paper]

Diffusion models

• "DiffuseMorph: Unsupervised Deformable Image Registration Using Diffusion Model", ECCV, 2022 (Kim et al.). [Paper][GitHub]
• "FSDiffReg: Feature-Wise and Score-Wise Diffusion-Guided Unsupervised Deformable Image Registration for Cardiac Images", MICCAI, 2023 (Qin and Li). [Paper][GitHub]

Neural ODEs

• "Multi-scale neural ODES for 3D medical image registration", MICCAI, 2021 (Xu et al.). [Paper]
• "NODEO: A Neural Ordinary Differential Equation Based Optimization Framework for Deformable Image Registration", CVPR, 2022 (Wu et al.). [Paper][GitHub]
• "R2Net: Efficient and flexible diffeomorphic image registration using Lipschitz continuous residual networks", MedIA, 2023 (Joshi and Hong). [Paper][GitHub]

Implicit neural representations

• "Diffeomorphic Image Registration With Neural Velocity Field", WACV, 2023 (Han et al.). [Paper]
• "Implicit neural representations for deformable image registration", MIDL, 2022 (Wolterink et al.). [Paper][GitHub]
• "Implicit neural representations for joint decomposition and registration of gene expression images in the marmoset brain", MICCAI, 2023 (Byra et al.). [Paper][GitHub]
• "Deformable Image Registration with Geometry-informed Implicit Neural Representations", MIDL, 2024 (van Harten et al.). [Paper][GitHub]
• "Topology-preserving shape reconstruction and registration via neural diffeomorphic flow", CVPR, 2022 (Sun et al.). [Paper][GitHub]

Hyperparameter conditioning

• "Learning the Effect of Registration Hyperparameters with HyperMorph", MELBA, 2022 (Hoopes et al.). [Paper][GitHub]
• "Conditional deformable image registration with convolutional neural network", MICCAI, 2021 (Mok et al.). [Paper][GitHub]
• "Spatially-varying Regularization with Conditional Transformer for Unsupervised Image Registration", ArXiv, 2023 (Chen et al.). [Paper][GitHub]

Anatomy-aware networks

• "Nonuniformly Spaced Control Points Based on Variational Cardiac Image Registration", MICCAI, 2023 (Su et al.). [Paper]
• "A deep discontinuity-preserving image registration network", MICCAI, 2021 (Chen et al.). [Paper][GitHub]

Correlation layer

• "Closing the gap between deep and conventional image registration using probabilistic dense displacement networks", MICCAI, 2019 (Heinrich). [Paper][GitHub]
• "Highly accurate and memory efficient unsupervised learning-based discrete CT registration using 2.5 D displacement search", MICCAI, 2020 (Heinrich and Hansen). [Paper][GitHub]
• "Voxelmorph++ going beyond the cranial vault with keypoint supervision and multi-channel instance optimisation", WBIR, 2022 (Heinrich and Hansen). [Paper][GitHub]
• "Fast 3D registration with accurate optimisation and little learning for Learn2Reg 2021", MIDOG, 2021 (Siebert et al.). [Paper][GitHub]
• $${\color{red}New!}$$ "ConvexAdam: Self-Configuring Dual-Optimisation-Based 3D Multitask Medical Image Registration", IEEE TMI, 2024 (Siebert et al.). [Paper][GitHub]

Progressive and pyramid registration

• "Unsupervised 3D end-to-end medical image registration with volume tweening network", IEEE JBHI, 2019 (Zhao et al.). [Paper][GitHub]
• "Learning a model-driven variational network for deformable image registration", IEEE TMI, 2021 (Jia et al.). [Paper][GitHub]
• "Unsupervised Learning of Diffeomorphic Image Registration via TransMorph", WBIR, 2022 (Chen et al.). [Paper][GitHub]
• "Deep learning-based image registration in dynamic myocardial perfusion CT imaging", IEEE TMI, 2023 (Lara-Hernandez et al.). [Paper]
• "A multi-scale framework with unsupervised joint training of convolutional neural networks for pulmonary deformable image registration", PMB, 2020 (Jiang et al.). [Paper]
• "Dual-stream pyramid registration network", MedIA, 2022 (Kang et al.). [Paper][GitHub]
• "Joint progressive and coarse-to-fine registration of brain MRI via deformation field integration and non-rigid feature fusion", IEEE TMI, 2022 (Lv et al.). [Paper][GitHub]
• "A deep learning framework for unsupervised affine and deformable image registration", MedIA, 2019 (de Vos et al.). [Paper][GitHub]
• "Progressively trained convolutional neural networks for deformable image registration", IEEE TMI, 2019 (Eppenhof et al.). [Paper]
• "Large deformation diffeomorphic image registration with laplacian pyramid networks", MICCAI, 2020 (Mok et al.). [Paper][GitHub]
• "Self-recursive contextual network for unsupervised 3D medical image registration", MLMI, 2020 (Hu et al.). [Paper]
• "Self-Distilled Hierarchical Network for Unsupervised Deformable Image Registration", IEEE TMI, 2023 (Zhou et al.). [Paper][GitHub]
• "Non-iterative Coarse-to-Fine Transformer Networks for Joint Affine and Deformable Image Registration", MICCAI, 2023 (Meng et al.). [Paper][GitHub]
• "PIViT: Large Deformation Image Registration with Pyramid-Iterative Vision Transformer", MICCAI, 2023 (Ma et al.). [Paper][GitHub]

Registration Uncertainty

• "On the applicability of registration uncertainty", MICCAI, 2019 (Luo et al.). [Paper]
• "Double-uncertainty guided spatial and temporal consistency regularization weighting for learning-based abdominal registration", MICCAI, 2022 (Xu et al.). [Paper]
• "Transmorph: Transformer for unsupervised medical image registration", MedIA, 2022 (Chen et al.). [Paper][GitHub]
• "Estimating medical image registration error and confidence: A taxonomy and scoping review", MedIA, 2022 (Bierbrier et al.). [Paper]
• "From Registration Uncertainty to Segmentation Uncertainty", ISBI, 2024 (Chen et al.). [Paper][GitHub]

Benchmark dataset for medical image registration

$${\color{red}New!}$$

Dataset	Anatomy	Cohort Type	Modality	Source
IXI	Brain	Healthy Controls	T1w, T2w, PDw MRI	Official Website
LUMIR	Brain	Healthy Controls	T1w MRI	Learn2Reg 2024
LPBA40	Brain	Healthy Controls	T1w MRI	Official Website
Mindboggle	Brain	Healthy Controls	T1w MRI	Official Website
OASIS	Brain	Alzheimer’s disease	T1w MRI	Official Website
BraTS-Reg	Brain	Glioma	T1w, T1ce, T2w, FLAIR MRI	Official Website
CuRIOUS	Brain	Glioma	T1w, T2-FLAIR MRI, 3D US	Learn2Reg 2020
ReMIND2Reg	Brain	Tumor resection	T1w, T2w MRI, 3D US	Learn2Reg 2024
Hippocampus-MR	Brain	Non-affective psychosis	T1w MRI	Learn2Reg 2020
DIR-Lab	Lung	COPD, cancer	Breath-hold and 4DCT	Official Website
NLST	Lung	Smokers	Spiral CT	Official Website
Lung-CT	Lung	Healthy Controls	Inspiratory, expiratory CT	Learn2Reg 2021
EMPIRE10	Lung	Healthy Controls	Inspiratory, expiratory CT	Official Website
Thorax-CBCT	Lung	Cancer Patients	CT, CBCT	Learn2Reg 2023
Lung250M-4B	Lung	Mixed	CT	Official Website
ACDC	Heart	Cardiac diseases	4D cine-MRI	Official Website
M&Ms	Heart	Cardiac diseases	4D cine-MRI	Official Website
MM-WHS	Heart	Cardiac diseases	CT, MRI	Official Website
Abdomen-CT-CT	Abdomen	Cancer Patients	CT	Learn2Reg 2020
Abdomen-MR-CT	Abdomen	Cancer Patients	CT, MR	Learn2Reg 2021
ACROBAT	Breast	Breast Cancer	Pathological images	Official Website
ANHIR	Body-wide	Cancer tissue samples	Pathological images	Official Website
COMULISglobe SHG-BF	Breast / Pancreas	Cancer tissue samples	Pathological images	Learn2Reg 2024
COMULISglobe 3D-CLEM	Cell	Mitochondria, nuclei	Microscopy	Learn2Reg 2024

Applications of Image Registration

Atlas construction

• "Learning conditional deformable templates with convolutional networks", NeurIPS, 2019 (Dalca et al.). [Paper][GitHub]
• "Generative adversarial registration for improved conditional deformable templates", CVPR, 2021 (Dey et al.). [Paper][GitHub]
• "Unbiased atlas construction for neonatal cortical surfaces via unsupervised learning", ASMUS&PIPPI, 2020 (Cheng et al.). [Paper]
• "Aladdin: Joint Atlas Building and Diffeomorphic Registration Learning with Pairwise Alignment", CVPR, 2022 (Ding and Niethammer). [Paper][GitHub]
• "Learning 4D infant cortical surface atlas with unsupervised spherical networks", MICCAI, 2021 (Zhao et al.). [Paper]
• "Towards a 4D Spatio-Temporal Atlas of the Embryonic and Fetal Brain Using a Deep Learning Approach for Groupwise Image Registration", WBIR, 2022 (Bastiaansen et al.). [Paper]
• "Learning conditional deformable shape templates for brain anatomy", MLMI, 2020 (Yu et al.). [Paper][GitHub]
• "Construction of longitudinally consistent 4D infant cerebellum atlases based on deep learning", MICCAI, 2021 (Chen et al.). [Paper]
• "CAS-Net: conditional atlas generation and brain segmentation for fetal MRI", UNSURE&PIPPI, 2021 (Liu et al.). [Paper]
• "Atlas-ISTN: joint segmentation, registration and atlas construction with image-and-spatial transformer networks", MedIA, 2022 (Sinclair et al.). [Paper][GitHub]
• "Hybrid Atlas Building with Deep Registration Priors", ISBI, 2022 (Wu et al.). [Paper]
• "Learning-based template synthesis for groupwise image registration", SASHIMI, 2021 (He and Chung). [Paper]
• "Learning spatiotemporal probabilistic atlas of fetal brains with anatomically constrained registration network", MICCAI, 2021 (Pei et al.). [Paper]
• "ImplicitAtlas: learning deformable shape templates in medical imaging", CVPR, 2022 (Yang et al.). [Paper]
• "GroupRegNet: a groupwise one-shot deep learning-based 4D image registration method", PMB, 2021 (Zhang et al.). [Paper][GitHub]
• "Groupwise Image Registration with Atlas of Multiple Resolutions Refined at Test Phase", MICCAI, 2023 (He et al.). [Paper]
• "Learning inverse consistent 3D groupwise registration with deforming autoencoders", SPIE:MI, 2021 (Siebert et al.). [Paper]
• "Geo-SIC: Learning Deformable Geometric Shapes in Deep Image Classifiers", NeurIPS, 2022 (Wang and Zhang). [Paper][GitHub]

Multi-atlas segmentation

• "Votenet: A deep learning label fusion method for multi-atlas segmentation", MICCAI, 2019 (Ding et al.). [Paper][GitHub]
• "Votenet+: An improved deep learning label fusion method for multi-atlas segmentation", ISBI, 2020 (Ding et al.). [Paper][GitHub]
• "Cross-Modality Multi-Atlas Segmentation via Deep Registration and Label Fusion", IEEE JBHI, 2022 (Ding et al.). [Paper][GitHub]
• "Multi-atlas segmentation and spatial alignment of the human embryo in first trimester 3D ultrasound", MELBA, 2022 (Bastiaansen et al.). [Paper][GitHub]
• "Atlas-ISTN: joint segmentation, registration and atlas construction with image-and-spatial transformer networks", MedIA, 2022 (Sinclair et al.). [Paper][GitHub]
• "Anatomically constrained and attention-guided deep feature fusion for joint segmentation and deformable medical image registration", MedIA, 2023 (Khor et al.). [Paper]
• "DeepAtlas: Joint semi-supervised learning of image registration and segmentation", MICCAI, 2019 (Xu and Niethammer). [Paper][GitHub]

Uncertainty

• "Deformable image registration uncertainty for inter-fractional dose accumulation of lung cancer proton therapy", RO, 2020 (Nenoff et al.). [Paper]

Motion estimation

• "Joint learning of motion estimation and segmentation for cardiac MR image sequences", MICCAI, 2018 (Qin et al.). [Paper][GitHub]
• "Implementation and validation of a three-dimensional cardiac motion estimation network", Radiology:AI, 2019 (Morales et al.). [Paper]
• "MulViMotion: Shape-aware 3D Myocardial Motion Tracking from Multi-View Cardiac MRI", IEEE TMI, 2022 (Meng et al.). [Paper][GitHub]
• "FOAL: Fast online adaptive learning for cardiac motion estimation", CVPR, 2020 (Yu et al.). [Paper]
• "Generative myocardial motion tracking via latent space exploration with biomechanics-informed prior", MedIA, 2023 (Qin et al.). [Paper][GitHub]
• "WarpPINN: Cine-MR image registration with physics-informed neural networks", MedIA, 2022 (L{'o}pez et al.). [Paper][GitHub]
• "DeepTag: An unsupervised deep learning method for motion tracking on cardiac tagging magnetic resonance images", CVPR, 2021 (Ye et al.). [Paper][GitHub]
• "DRIMET: Deep registration-based 3D incompressible motion estimation in Tagged-MRI with application to the tongue", MIDL, 2024 (Bian et al.). [Paper][GitHub]
• "Momentamorph: Unsupervised spatial-temporal registration with momenta, shooting, and correction", MICCAI, 2023 (Bian et al.). [Paper]
• "A semi-supervised joint network for simultaneous left ventricular motion tracking and segmentation in 4D echocardiography", MICCAI, 2020 (Ta et al.). [Paper]
• "Unsupervised motion tracking of left ventricle in echocardiography", SPIE:MI, 2020 (Ahn et al.). [Paper]
• "LungRegNet: an unsupervised deformable image registration method for 4D-CT lung", Med. Phys., 2020 (Fu et al.). [Paper]
• "An unsupervised image registration method employing chest computed tomography images and deep neural networks", CBM, 2023 (Ho et al.). [Paper]
• "One-shot learning for deformable medical image registration and periodic motion tracking", IEEE TMI, 2020 (Fechter and Baltas). [Paper][GitHub]
• "CNN-based lung CT registration with multiple anatomical constraints", MedIA, 2021 (Hering et al.). [Paper][Code]
• "A One-shot Lung 4D-CT Image Registration Method with Temporal-spatial Features", BioCAS, 2022 (Ji et al.). [Paper]
• "ORRN: An ODE-based Recursive Registration Network for Deformable Respiratory Motion Estimation With Lung 4DCT Images", IEEE TBME, 2023 (Liang et al.). [Paper][GitHub]

2D-3D registration

• "The impact of machine learning on 2D/3D registration for image-guided interventions: A systematic review and perspective", FRAI, 2021 (Unberath et al.). [Paper]
• "Extended Capture Range of Rigid 2D/3D Registration by Estimating Riemannian Pose Gradients", MLMI, 2020 (Gu et al.). [Paper]
• "Multiview 2D/3D rigid registration via a point-of-interest network for tracking and triangulation", CVPR, 2019 (Liao et al.). [Paper]
• "Generalizing spatial transformers to projective geometry with applications to 2D/3D registration", MICCAI, 2020 (Gao et al.). [Paper][GitHub]
• "Fiducial-free 2D/3D registration of the proximal femur for robot-assisted femoroplasty", SPIE:MI, 2020 (Gao et al.). [Paper]
• "Self-Supervised 2D/3D Registration for X-Ray to CT Image Fusion", WACV, 2019 (Jaganathan et al.). [Paper]
• "A Novel Two-Stage Framework for 2D/3D Registration in Neurological Interventions", ROBIO, 2022 (Huang et al.). [Paper]
• "X-ray to ct rigid registration using scene coordinate regression", MICCAI, 2023 (Shrestha et al.). [Paper][GitHub]
• "Extremely dense point correspondences using a learned feature descriptor", CVPR, 2020 (Liu et al.). [Paper][GitHub]
• "Colonoscopy 3D Video Dataset with Paired Depth from 2D-3D Registration", MedIA, 2023 (Bobrow et al.). [Paper][GitHub]
• "StructuRegNet: Structure-Guided Multimodal 2D-3D Registration", MICCAI, 2023 (Leroy et al.). [Paper]
• "A deep learning approach for 2D ultrasound and 3D CT/MR image registration in liver tumor ablation", CMPB, 2021 (Wei et al.). [Paper]
• "Multimodal registration of ultrasound and MR images using weighted self-similarity structure vector", CBM, 2023 (Wang et al.). [Paper]
• "Ultrasound Frame-to-Volume Registration via Deep Learning for Interventional Guidance", IEEE TUFFC, 2022 (Guo et al.). [Paper][GitHub]
• "A patient-specific self-supervised model for automatic X-Ray/CT registration", MICCAI, 2023 (Zhang et al.). [Paper][GitHub]
• "X-ray to DRR images translation for efficient multiple objects similarity measures in deformable model 3D/2D registration", IEEE TMI, 2022 (Aubert et al.). [Paper]
• "Learning Expected Appearances for Intraoperative Registration during Neurosurgery", MICCAI, 2023 (Haouchine et al.). [Paper][GitHub]
• "Non-Rigid 2D-3D Registration Using Convolutional Autoencoders", ISBI, 2020 (Li et al.). [Paper]

Towards Zero-shot Registration or Fundation Models

• "SynthMorph: learning contrast-invariant registration without acquired images", IEEE TMI, 2021 (Hoffmann et al.). [Paper][GitHub]
• "Unsupervised 3D registration through optimization-guided cyclical self-training", MICCAI, 2023 (Bigalke et al.). [Paper][GitHub]
• "uniGradICON: A Foundation Model for Medical Image Registration", MICCAI, 2024 (Tian et al.). [Paper][GitHub]
• "BrainMorph: A Foundational Keypoint Model for Robust and Flexible Brain MRI Registration", ArXiv, 2024 (Wang et al.). [Paper][GitHub]
• $${\color{red}New!}$$ "multiGradICON: A Foundation Model for Multimodal Medical Image Registration", ArXiv, 2024 (Demir et al.). [Paper][GitHub]

Trends in image registration-related research based on PubMed paper counts

• Learning-based image registration research:
  • Search query: ("image registration"[Title/Abstract] OR "image alignment"[Title/Abstract]) AND ("Neural Networks"[Title/Abstract] OR "Neural Network"[Title/Abstract] OR "DNN"[Title/Abstract] OR "CNN"[Title/Abstract] OR "ConvNet"[Title/Abstract] OR "Deep Learning"[Title/Abstract] OR "Transformer"[Title/Abstract])
  • PubMed Link
• Unsupervised learning-based image registration research:
  • Search query: ("Unsupervised"[Title/Abstract] OR "end to end"[Title/Abstract]) AND ("Image Registration"[Title/Abstract] OR "Image Alignment"[Title/Abstract]) AND ("Neural Networks"[Title/Abstract] OR "Neural Network"[Title/Abstract] OR "DNN"[Title/Abstract] OR "CNN"[Title/Abstract] OR "ConvNet"[Title/Abstract] OR "Deep Learning"[Title/Abstract] OR "Transformer"[Title/Abstract])
  • PubMed Link