Papers Medical Image Registration
“Medical Image Registration” 태그가 달린 논문 228편 · 필터 해제
NCF: Neural Correspondence Field for Medical Image Registration
Deformable image registration is a fundamental task in medical image processing. Traditional optimization-based methods often struggle with accuracy in dealing with complex deformation. Recently, learning-based methods h…
Image RegistrationMedical Image RegistrationTriad: Vision Foundation Model for 3D Magnetic Resonance Imaging
Vision foundation models (VFMs) are pre-trained on extensive image datasets to learn general representations for diverse types of data. These models can subsequently be fine-tuned for specific downstream tasks, significa…
Cancer ClassificationComputed Tomography (CT)Image RegistrationMedical Image Registration+1Medical Image Registration Meets Vision Foundation Model: Prototype Learning and Contour Awareness
Medical image registration is a fundamental task in medical image analysis, aiming to establish spatial correspondences between paired images. However, existing unsupervised deformable registration methods rely solely on…
Image RegistrationMedical Image AnalysisMedical Image RegistrationSegmentationAdvancing Deformable Medical Image Registration with Multi-axis Cross-covariance Attention
Deformable image registration is a fundamental requirement for medical image analysis. Recently, transformers have been widely used in deep learning-based registration methods for their ability to capture long-range depe…
Deformable Medical Image RegistrationImage RegistrationMedical Image AnalysisMedical Image RegistrationFrom Model Based to Learned Regularization in Medical Image Registration: A Comprehensive Review
Image registration is fundamental in medical imaging applications, such as disease progression analysis or radiation therapy planning. The primary objective of image registration is to precisely capture the deformation b…
Image RegistrationMedical Image RegistrationLDM-Morph: Latent diffusion model guided deformable image registration
Deformable image registration plays an essential role in various medical image tasks. Existing deep learning-based deformable registration frameworks primarily utilize convolutional neural networks (CNNs) or Transformers…
Computational EfficiencyImage RegistrationMedical Image RegistrationMORPHA Symmetric Dynamic Learning Framework for Diffeomorphic Medical Image Registration
Diffeomorphic image registration is crucial for various medical imaging applications because it can preserve the topology of the transformation. This study introduces DCCNN-LSTM-Reg, a learning framework that evolves dyn…
Diffeomorphic Medical Image RegistrationImage RegistrationMedical Image RegistrationNCA-Morph: Medical Image Registration with Neural Cellular Automata
Medical image registration is a critical process that aligns various patient scans, facilitating tasks like diagnosis, surgical planning, and tracking. Traditional optimization based methods are slow, prompting the use o…
HippocampusImage RegistrationMedical Image RegistrationMORPHUTSRMorph: A Unified Transformer and Superresolution Network for Unsupervised Medical Image Registration
Complicated image registration is a key issue in medical image analysis, and deep learning-based methods have achieved better results than traditional methods. The methods include ConvNet-based and Transformer-based meth…
DecoderImage RegistrationMedical Image AnalysisMedical Image Registration+2GESH-Net: Graph-Enhanced Spherical Harmonic Convolutional Networks for Cortical Surface Registration
Currently, cortical surface registration techniques based on classical methods have been well developed. However, a key issue with classical methods is that for each pair of images to be registered, it is necessary to se…
Deep LearningGraph AttentionImage RegistrationMedical Image RegistrationSAMReg: SAM-enabled Image Registration with ROI-based Correspondence
This paper describes a new spatial correspondence representation based on paired regions-of-interest (ROIs), for medical image registration. The distinct properties of the proposed ROI-based correspondence are discussed,…
Image RegistrationMedical Image RegistrationPrompt EngineeringSegmentationRayEmb: Arbitrary Landmark Detection in X-Ray Images Using Ray Embedding Subspace
Intra-operative 2D-3D registration of X-ray images with pre-operatively acquired CT scans is a crucial procedure in orthopedic surgeries. Anatomical landmarks pre-annotated in the CT volume can be detected in X-ray image…
Medical Image RegistrationNestedMorph: Enhancing Deformable Medical Image Registration with Nested Attention Mechanisms
Deformable image registration is crucial for aligning medical images in a nonlinear fashion across different modalities, allowing for precise spatial correspondence between varying anatomical structures. This paper prese…
DecoderDeformable Medical Image RegistrationDiffusion MRIImage Registration+2Dual-Attention Frequency Fusion at Multi-Scale for Joint Segmentation and Deformable Medical Image Registration
Deformable medical image registration is a crucial aspect of medical image analysis. In recent years, researchers have begun leveraging auxiliary tasks (such as supervised segmentation) to provide anatomical structure in…
DecoderDeformable Medical Image RegistrationImage RegistrationMedical Image Analysis+3Unsupervised Multimodal 3D Medical Image Registration with Multilevel Correlation Balanced 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…
global-optimizationImage RegistrationMedical Image RegistrationH-SGANet: Hybrid Sparse Graph Attention Network for Deformable Medical Image Registration
The integration of Convolutional Neural Network (ConvNet) and Transformer has emerged as a strong candidate for image registration, leveraging the strengths of both models and a large parameter space. However, this hybri…
Deformable Medical Image RegistrationGPUGraph AttentionGraph Neural Network+2Reliable Multi-modal Medical Image-to-image Translation Independent of Pixel-wise Aligned Data
The current mainstream multi-modal medical image-to-image translation methods face a contradiction. Supervised methods with outstanding performance rely on pixel-wise aligned training data to constrain the model optimiza…
Image RegistrationImage-to-Image TranslationMedical Image RegistrationModel Optimization+1Deep Learning in Medical Image Registration: Magic or Mirage?
Classical optimization and learning-based methods are the two reigning paradigms in deformable image registration. While optimization-based methods boast generalizability across modalities and robust performance, learnin…
Deep LearningImage RegistrationMedical Image RegistrationmultiGradICON: A Foundation Model for Multimodal Medical Image Registration
Modern medical image registration approaches predict deformations using deep networks. These approaches achieve state-of-the-art (SOTA) registration accuracy and are generally fast. However, deep learning (DL) approaches…
AnatomyDeep LearningImage RegistrationMedical Image RegistrationWiNet: Wavelet-based Incremental Learning for Efficient Medical Image Registration
Deep image registration has demonstrated exceptional accuracy and fast inference. Recent advances have adopted either multiple cascades or pyramid architectures to estimate dense deformation fields in a coarse-to-fine ma…
GPUImage RegistrationIncremental LearningMedical Image Registration