Papers Medical Image Registration
“Medical Image Registration” 태그가 달린 논문 228편 · 필터 해제
DARE: A Deformable Adaptive Regularization Estimator for Learning-Based Medical Image Registration
Deformable medical image registration is a fundamental task in medical image analysis. While deep learning-based methods have demonstrated superior accuracy and computational efficiency compared to traditional techniques…
Medical Image RegistrationComputational EfficiencyiPEAR: Iterative Pyramid Estimation with Attention and Residuals for Deformable Medical Image Registration
Existing pyramid registration networks may accumulate anatomical misalignments and lack an effective mechanism to dynamically determine the number of optimization iterations under varying deformation requirements across …
Medical Image RegistrationUncertainty Estimation for Pretrained Medical Image Registration Models via Transformation Equivariance
Accurate image registration is essential in many medical imaging applications, yet most deep registration networks provide little indication of when or where their predictions are unreliable. Existing uncertainty estimat…
Medical Image RegistrationSAMIR, an efficient registration framework via robust feature learning from SAM
Image registration is a fundamental task in medical image analysis. Deformations are often closely related to the morphological characteristics of tissues, making accurate feature extraction crucial. Recent weakly superv…
Medical Image RegistrationRepresentation LearningSurrogate Supervision for Robust and Generalizable Deformable Image Registration
Objective: Deep learning-based deformable image registration has achieved strong accuracy, but remains sensitive to variations in input image characteristics such as artifacts, field-of-view mismatch, or modality differe…
Medical Image RegistrationLearn2Reg 2024: New Benchmark Datasets Driving Progress on New Challenges
Medical image registration is critical for clinical applications, and fair benchmarking of different methods is essential for monitoring ongoing progress in the field. To date, the Learn2Reg 2020-2023 challenges have rel…
Medical Image RegistrationTCFNet: Bidirectional face-bone transformation via a Transformer-based coarse-to-fine point movement network
Computer-aided surgical simulation is a critical component of orthognathic surgical planning, where accurately simulating face-bone shape transformations is significant. The traditional biomechanical simulation methods a…
Medical Image RegistrationPoint CloudsDINOv3 with Test-Time Training for Medical Image Registration
Prior medical image registration approaches, particularly learning-based methods, often require large amounts of training data, which constrains clinical adoption. To overcome this limitation, we propose a training-free …
Medical Image RegistrationModality-Aware Feature Matching in Visual and Vision-Language Applications: A Comprehensive Survey
Feature matching is a cornerstone task in computer vision, essential for applications such as image retrieval, stereo matching, 3D reconstruction, and SLAM. This survey comprehensively reviews modality-based feature matc…
Medical Image Registration3D ReconstructionImage RetrievalImage MatchingAre Vision Foundation Models Ready for Out-of-the-Box Medical Image Registration?
Foundation models, pre-trained on large image datasets and capable of capturing rich feature representations, have recently shown potential for zero-shot image registration. However, their performance has mostly been tes…
AnatomyImage RegistrationMedical Image RegistrationBridging Classical and Learning-based Iterative Registration through Deep Equilibrium Models
Deformable medical image registration is traditionally formulated as an optimization problem. While classical methods solve this problem iteratively, recent learning-based approaches use recurrent neural networks (RNNs) …
Medical Image RegistrationDeformable Medical Image Registration with Effective Anatomical Structure Representation and Divide-and-Conquer Network
Effective representation of Regions of Interest (ROI) and independent alignment of these ROIs can significantly enhance the performance of deformable medical image registration (DMIR). However, current learning-based DMI…
Deformable Medical Image RegistrationHippocampusImage RegistrationMedical Image RegistrationImplicit Deformable Medical Image Registration with Learnable Kernels
Deformable medical image registration is an essential task in computer-assisted interventions. This problem is particularly relevant to oncological treatments, where precise image alignment is necessary for tracking tumo…
Deformable Medical Image RegistrationImage RegistrationMedical Image RegistrationPretraining Deformable Image Registration Networks with Random Images
Recent advances in deep learning-based medical image registration have shown that training deep neural networks~(DNNs) does not necessarily require medical images. Previous work showed that DNNs trained on randomly gener…
Computational EfficiencyImage RegistrationMedical Image RegistrationImproving Generalization of Medical Image Registration Foundation Model
Deformable registration is a fundamental task in medical image processing, aiming to achieve precise alignment by establishing nonlinear correspondences between images. Traditional methods offer good adaptability and int…
Computational EfficiencyImage RegistrationMedical Image RegistrationFF-PNet: A Pyramid Network Based on Feature and Field for Brain Image Registration
In recent years, deformable medical image registration techniques have made significant progress. However, existing models still lack efficiency in parallel extraction of coarse and fine-grained features. To address this…
Deformable Medical Image RegistrationImage RegistrationMedical Image RegistrationTetrahedron-Net for Medical Image Registration
Medical image registration plays a vital role in medical image processing. Extracting expressive representations for medical images is crucial for improving the registration quality. One common practice for this end is c…
DecoderImage RegistrationMedical Image RegistrationIMPACT: A Generic Semantic Loss for Multimodal Medical Image Registration
Image registration is fundamental in medical imaging, enabling precise alignment of anatomical structures for diagnosis, treatment planning, image-guided interventions, and longitudinal monitoring. This work introduces I…
Deformable Medical Image RegistrationImage RegistrationMedical Image RegistrationSemantic Similarity+1OncoReg: Medical Image Registration for Oncological Challenges
In modern cancer research, the vast volume of medical data generated is often underutilised due to challenges related to patient privacy. The OncoReg Challenge addresses this issue by enabling researchers to develop and …
Image RegistrationMedical Image RegistrationSACB-Net: Spatial-awareness Convolutions for Medical Image Registration
Deep learning-based image registration methods have shown state-of-the-art performance and rapid inference speeds. Despite these advances, many existing approaches fall short in capturing spatially varying information in…
Image RegistrationMedical Image Registration