Papers Medical Image Registration
“Medical Image Registration” 태그가 달린 논문 228편 · 필터 해제
RIPE++: Reinforced Keypoint Learning from Positive Pairs Only
Sparse keypoint extraction and matching underpin core tasks in geometric computer vision, including structure-from-motion, visual SLAM, augmented reality, and medical image registration. Learning robust local feature rep…
Medical Image RegistrationRepresentation LearningReinforcement LearningThe Right Prior for the Right Deformation: Rethinking Continuous Deformable Image Registration
Deformable image registration models implicitly encode deformation priors through their parametrization and optimization. In this work, we conduct a validation study on continuous registration methods to examine how thes…
Medical Image RegistrationDrivenMorph: Bridging Attention Mechanism and Variational Image Registration via Difference Modeling
Medical image registration benefits significantly from deep learning, yet existing approaches often lack physical explainability and fine-grained deformation control. Motivated by Demons algorithms, we propose a novel Dr…
Medical Image RegistrationSpikeReg: Energy-Efficient 3D Deformable Medical Image Registration with Spiking Neural Networks
Deformable medical image registration aligns anatomical structures across images but remains computationally dense at 3D resolution. Spiking neural networks (SNNs) offer sparse event-driven computation, yet have not been…
Medical Image RegistrationSearch-MIND: Training-Free Multi-Modal Medical Image Registration
Multi-modal image registration plays a critical role in precision medicine but faces challenges from non-linear intensity relationships and local optima. While deep learning models enable rapid inference, they often suff…
Medical Image RegistrationCoRe: Joint Optimization with Contrastive Learning for Medical Image Registration
Medical image registration is a fundamental task in medical image analysis, enabling the alignment of images from different modalities or time points. However, intensity inconsistencies and nonlinear tissue deformations …
Medical Image RegistrationRepresentation LearningContrastive LearningOn the Degrees of Freedom of Gridded Control Points in Learning-Based Medical Image Registration
Many registration problems are ill-posed in homogeneous or noisy regions, and dense voxel-wise decoders can be unnecessarily high-dimensional. A sparse control-point parameterisation provides a compact, smooth deformatio…
Medical Image RegistrationEffective Feature Learning for 3D Medical Registration via Domain-Specialized DINO Pretraining
Medical image registration is a critical component of clinical imaging workflows, enabling accurate longitudinal assessment, multi-modal data fusion, and image-guided interventions. Intensity-based approaches often strug…
Medical Image RegistrationPolaffini: A feature-based approach for robust affine and polyaffine image registration
In this work we present Polaffini, a robust and versatile framework for anatomically grounded registration. Medical image registration is dominated by intensity-based registration methods that rely on surrogate measures …
Medical Image RegistrationUnsupervised MR-US Multimodal Image Registration with Multilevel Correlation Pyramidal Optimization
Surgical navigation based on multimodal image registration has played a significant role in providing intraoperative guidance to surgeons by showing the relative position of the target area to critical anatomical structu…
Medical Image RegistrationAttention-Driven Framework for Non-Rigid Medical Image Registration
Deformable medical image registration is a fundamental task in medical image analysis with applications in disease diagnosis, treatment planning, and image-guided interventions. Despite significant advances in deep learn…
Medical Image RegistrationComputational EfficiencyLDRNet: Large Deformation Registration Model for Chest CT Registration
Most of the deep learning based medical image registration algorithms focus on brain image registration tasks.Compared with brain registration, the chest CT registration has larger deformation, more complex background an…
Medical Image RegistrationInterpretable Unsupervised Deformable Image Registration via Confidence-bound Multi-Hop Visual Reasoning
Unsupervised deformable image registration requires aligning complex anatomical structures without reference labels, making interpretability and reliability critical. Existing deep learning methods achieve considerable a…
Medical Image RegistrationVisual ReasoningFMIR, a foundation model-based Image Registration Framework for Robust Image Registration
Deep learning has revolutionized medical image registration by achieving unprecedented speeds, yet its clinical application is hindered by a limited ability to generalize beyond the training domain, a critical weakness g…
Medical Image RegistrationDynamic Stream Network for Combinatorial Explosion Problem in Deformable Medical Image Registration
Combinatorial explosion problem caused by dual inputs presents a critical challenge in Deformable Medical Image Registration (DMIR). Since DMIR processes two images simultaneously as input, the combination relationships …
Medical Image RegistrationTest Time Optimized Generalized AI-based Medical Image Registration Method
Medical image registration is critical for aligning anatomical structures across imaging modalities such as computed tomography (CT), magnetic resonance imaging (MRI), and ultrasound. Among existing techniques, non-rigid…
Medical Image RegistrationMedDIFT: Multi-Scale Diffusion-Based Correspondence in 3D Medical Imaging
Accurate spatial correspondence between medical images is essential for longitudinal analysis, lesion tracking, and image-guided interventions. Medical image registration methods rely on local intensity-based similarity …
Medical Image RegistrationRobust Rigid and Non-Rigid Medical Image Registration Using Learnable Edge Kernels
Medical image registration is crucial for various clinical and research applications including disease diagnosis or treatment planning which require alignment of images from different modalities, time points, or subjects…
Medical Image RegistrationEdge DetectionDisentangling Progress in Medical Image Registration: Beyond Trend-Driven Architectures towards Domain-Specific Strategies
Medical image registration drives quantitative analysis across organs, modalities, and patient populations. Recent deep learning methods often combine low-level "trend-driven" computational blocks from computer vision, s…
Medical Image RegistrationEfficient Large-Deformation Medical Image Registration via Recurrent Dynamic Correlation
Deformable image registration estimates voxel-wise correspondences between images through spatial transformations, and plays a key role in medical imaging. While deep learning methods have significantly reduced runtime, …
Medical Image Registration