Papers Unsupervised Image Registration
“Unsupervised Image Registration” 태그가 달린 논문 22편 · 필터 해제
IMPACT: 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+1MORPH-LER: Log-Euclidean Regularization for Population-Aware Image Registration
Spatial transformations that capture population-level morphological statistics are critical for medical image analysis. Commonly used smoothness regularizers for image registration fail to integrate population statistics…
Image RegistrationMedical Image AnalysisMORPHUnsupervised Image RegistrationUTSRMorph: 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+2Deformable Image Registration with Multi-scale Feature Fusion from Shared Encoder, Auxiliary and Pyramid Decoders
In this work, we propose a novel deformable convolutional pyramid network for unsupervised image registration. Specifically, the proposed network enhances the traditional pyramid network by adding an additional shared au…
DecoderImage RegistrationUnsupervised Image RegistrationAdaptive Correspondence Scoring for Unsupervised Medical Image Registration
We propose an adaptive training scheme for unsupervised medical image registration. Existing methods rely on image reconstruction as the primary supervision signal. However, nuisance variables (e.g. noise and covisibilit…
Image ReconstructionImage RegistrationMedical Image RegistrationUnsupervised Image RegistrationResidual Aligner-based Network (RAN): Motion-separable structure for coarse-to-fine discontinuous deformable registration
Deformable image registration, the estimation of the spatial transformation between different images, is an important task in medical imaging. Deep learning techniques have been shown to perform 3D image registration eff…
Computed Tomography (CT)Deformable Medical Image RegistrationImage RegistrationMedical Image Registration+1High-resolution 3D Maps of Left Atrial Displacements using an Unsupervised Image Registration Neural Network
Functional analysis of the left atrium (LA) plays an increasingly important role in the prognosis and diagnosis of cardiovascular diseases. Echocardiography-based measurements of LA dimensions and strains are useful biom…
Image RegistrationPrognosisUnsupervised Image RegistrationFourier-Net+: Leveraging Band-Limited Representation for Efficient 3D Medical Image Registration
U-Net style networks are commonly utilized in unsupervised image registration to predict dense displacement fields, which for high-resolution volumetric image data is a resource-intensive and time-consuming task. To tack…
DecoderImage RegistrationMedical Image RegistrationUnsupervised Image RegistrationVista-Morph: Unsupervised Image Registration of Visible-Thermal Facial Pairs
For a variety of biometric cross-spectral tasks, Visible-Thermal (VT) facial pairs are used. However, due to a lack of calibration in the lab, photographic capture between two different sensors leads to severely misalign…
Image RegistrationMORPHPerson Re-IdentificationUnsupervised Image RegistrationRFR-WWANet: Weighted Window Attention-Based Recovery Feature Resolution Network for Unsupervised Image Registration
The Swin transformer has recently attracted attention in medical image analysis due to its computational efficiency and long-range modeling capability. Owing to these properties, the Swin Transformer is suitable for esta…
Computational EfficiencyImage RegistrationLong-range modelingMedical Image Analysis+1Spatially-varying Regularization with Conditional Transformer for Unsupervised Image Registration
In the past, optimization-based registration models have used spatially-varying regularization to account for deformation variations in different image regions. However, deep learning-based registration models have mostl…
Image RegistrationUnsupervised Image RegistrationFourier-Net: Fast Image Registration with Band-limited Deformation
Unsupervised image registration commonly adopts U-Net style networks to predict dense displacement fields in the full-resolution spatial domain. For high-resolution volumetric image data, this process is however resource…
DecoderImage RegistrationMedical Image RegistrationUnsupervised Image RegistrationSymmetric Transformer-based Network for Unsupervised Image Registration
Medical image registration is a fundamental and critical task in medical image analysis. With the rapid development of deep learning, convolutional neural networks (CNN) have dominated the medical image registration fiel…
DecoderImage RegistrationMedical Image AnalysisMedical Image Registration+1Unsupervised Image Registration Towards Enhancing Performance and Explainability in Cardiac And Brain Image Analysis
Magnetic Resonance Imaging (MRI) typically recruits multiple sequences (defined here as "modalities"). As each modality is designed to offer different anatomical and functional clinical information, there are evident dis…
Image GenerationImage RegistrationMedical Image AnalysisUnsupervised Image RegistrationLeveraging Unsupervised Image Registration for Discovery of Landmark Shape Descriptor
In current biological and medical research, statistical shape modeling (SSM) provides an essential framework for the characterization of anatomy/morphology. Such analysis is often driven by the identification of a relati…
AnatomyDimensionality ReductionImage RegistrationImage Segmentation+3A low-rank representation for unsupervised registration of medical images
Registration networks have shown great application potentials in medical image analysis. However, supervised training methods have a great demand for large and high-quality labeled datasets, which is time-consuming and s…
Image RegistrationMedical Image AnalysisUnsupervised Image RegistrationFlowReg: Fast Deformable Unsupervised Medical Image Registration using Optical Flow
We propose FlowReg, a deep learning-based framework for unsupervised image registration for neuroimaging applications. The system is composed of two architectures that are trained sequentially: FlowReg-A which affinely c…
AnatomyImage RegistrationMedical Image RegistrationOptical Flow Estimation+1DRMIME: Differentiable Mutual Information and Matrix Exponential for Multi-Resolution Image Registration
In this work, we present a novel unsupervised image registration algorithm. It is differentiable end-to-end and can be used for both multi-modal and mono-modal registration. This is done using mutual information (MI) as …
Image RegistrationUnsupervised Image RegistrationZero Shot Learning for Multi-Modal Real Time Image Registration
In this report we present an unsupervised image registration framework, using a pre-trained deep neural network as a feature extractor. We refer this to zero-shot learning, due to nonoverlap between training and testing …
Image RegistrationMedical Image RegistrationUnsupervised Image RegistrationZero-Shot LearningA Cooperative Autoencoder for Population-Based Regularization of CNN Image Registration
Spatial transformations are enablers in a variety of medical image analysis applications that entail aligning images to a common coordinate systems. Population analysis of such transformations is expected to capture the …
Computational EfficiencyImage RegistrationMedical Image AnalysisUnsupervised Image Registration