Deep Learning in Medical Image Registration: A Review

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 potentials. We provided a comprehensive comparison among DL-based methods for lung and brain deformable registration using benchmark datasets. Lastly, we analyzed the statistics of all the cited works from various aspects, revealing the popularity and future trend of development in medical image registration using deep learning.

32 pages, 4 figures, 9 tables

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Cited by in corpus (43)

• A review of deep learning in medical imaging: Imaging traits, technology trends, case studies with progress highlights, and future promises
• Recent advances and clinical applications of deep learning in medical image analysis
• Review: Deep Learning in Electron Microscopy
• Medical image registration using unsupervised deep neural network: A scoping literature review
• ModeT: Learning Deformable Image Registration via Motion Decomposition Transformer
• Landmark Tracking in Liver US images Using Cascade Convolutional Neural Networks with Long Short-Term Memory
• DeepReg: a deep learning toolkit for medical image registration
• LAPNet: Non-rigid Registration derived in k-space for Magnetic Resonance Imaging
• From Screens to Scenes: A Survey of Embodied AI in Healthcare
• Anatomy-aware and acquisition-agnostic joint registration with SynthMorph
• Fast computation of mutual information in the frequency domain with applications to global multimodal image alignment
• AFFIRM: Affinity Fusion-based Framework for Iteratively Random Motion correction of multi-slice fetal brain MRI
• Is Image-to-Image Translation the Panacea for Multimodal Image Registration? A Comparative Study
• FDRN: A Fast Deformable Registration Network for Medical Images
• Federated Split Vision Transformer for COVID-19 CXR Diagnosis using Task-Agnostic Training
• Deep Learning Analysis of Cardiac MRI in Legacy Datasets: Multi-Ethnic Study of Atherosclerosis
• A Deep Registration Method for Accurate Quantification of Joint Space Narrowing Progression in Rheumatoid Arthritis
• Probabilistic feature extraction, dose statistic prediction and dose mimicking for automated radiation therapy treatment planning
• CartiMorph: a framework for automated knee articular cartilage morphometrics
• Generative Aging of Brain Images with Diffeomorphic Registration
• Volumetric parcellation of the right ventricle for regional geometric and functional assessment
• Recursive Refinement Network for Deformable Lung Registration between Exhale and Inhale CT Scans
• Knowledge-based Radiation Treatment Planning: A Data-driven Method Survey
• FAS-UNet: A Novel FAS-driven Unet to Learn Variational Image Segmentation
• The use of deep learning in interventional radiotherapy (brachytherapy): a review with a focus on open source and open data
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• Deep Implicit Optimization enables Robust Learnable Features for Deformable Image Registration
• Morphology-based non-rigid registration of coronary computed tomography and intravascular images through virtual catheter path optimization
• Deep Learning in Multi-organ Segmentation
• INSPIRE: Intensity and spatial information-based deformable image registration
• Registration of serial sections: An evaluation method based on distortions of the ground truths
• Generative Adversarial Network for Image Synthesis
• Deformable Image Registration using Unsupervised Deep Learning for CBCT-guided Abdominal Radiotherapy
• ModeTv2: GPU-accelerated Motion Decomposition Transformer for Pairwise Optimization in Medical Image Registration
• Deep Image Reconstruction using Unregistered Measurements without Groundtruth
• RFR-WWANet: Weighted Window Attention-Based Recovery Feature Resolution Network for Unsupervised Image Registration
• F3RNet: Full-Resolution Residual Registration Network for Deformable Image Registration
• Impact of PCA-based preprocessing and different CNN structures on deformable registration of sonograms
• DiffFit: Visually-Guided Differentiable Fitting of Molecule Structures to a Cryo-EM Map
• Diffeomorphic Transformations for Time Series Analysis: An Efficient Approach to Nonlinear Warping
• Advancing biological super-resolution microscopy through deep learning: a brief review
• MICS : Multi-steps, Inverse Consistency and Symmetric deep learning registration network
• Employing similarity to highlight differences: On the impact of anatomical assumptions in chest X-ray registration methods