Image Registration
236 papers with code • 5 benchmarks • 12 datasets
Image registration is the process of transforming different sets of data into one coordinate system. Data may be multiple photographs, data from different sensors, times, depths, or viewpoints. It is used in computer vision, medical imaging, and compiling and analyzing images and data from satellites. Registration is necessary in order to be able to compare or integrate the data obtained from these different measurements.
Source: Image registration | Wikipedia
( Image credit: Kornia )
Benchmarks
These leaderboards are used to track progress in Image Registration
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Libraries
Use these libraries to find Image Registration models and implementationsDatasets
Medical Segmentation Decathlon
LLVIP
Learn2Reg
SegTHOR
UDIS-D
FIRE
DIR-LAB COPDgene
ALTO
Fetoscopy Placenta Data
FetReg: Largescale Multi-centre Fetoscopy Placenta Dataset
Latest papers
Decoder-Only Image Registration
xi-jia/lessnet
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For this, we propose a novel network architecture, termed LessNet in this paper, which contains only a learnable decoder, while entirely omitting the utilization of a learnable encoder.
Local Feature Matching Using Deep Learning: A Survey
The objective of this endeavor is to furnish a comprehensive overview of local feature matching methods.
MambaMorph: a Mamba-based Framework for Medical MR-CT Deformable Registration
Capturing voxel-wise spatial correspondence across distinct modalities is crucial for medical image analysis.
IVIM-Morph: Motion-compensated quantitative Intra-voxel Incoherent Motion (IVIM) analysis for functional fetal lung maturity assessment from diffusion-weighted MRI data
technioncomputationalmrilab/qdwi-morph
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IVIM-morph combines two sub-networks, a registration sub-network, and an IVIM model fitting sub-network, enabling simultaneous estimation of IVIM model parameters and motion.
High-Resolution Maps of Left Atrial Displacements and Strains Estimated with 3D CINE MRI and Unsupervised Neural Networks
We create maps of LA Displacement Vector Field (DVF) magnitude and LA principal strain values from images of 10 healthy volunteers and 8 patients with cardiovascular disease (CVD).
Intraoperative 2D/3D Image Registration via Differentiable X-ray Rendering
Preoperatively, a CNN is trained to regress the pose of a randomly oriented synthetic X-ray rendered from the preoperative CT.
DG-TTA: Out-of-domain medical image segmentation through Domain Generalization and Test-Time Adaptation
In this study, we propose to combine domain generalization and test-time adaptation to create a highly effective approach for reusing pre-trained models in unseen target domains.
Spatially Covariant Image Registration with Text Prompts
tinymilky/NeRD
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Medical images are often characterized by their structured anatomical representations and spatially inhomogeneous contrasts.
SAME++: A Self-supervised Anatomical eMbeddings Enhanced medical image registration framework using stable sampling and regularized transformation
In this work, we introduce a fast and accurate method for unsupervised 3D medical image registration building on top of a Self-supervised Anatomical eMbedding (SAM) algorithm, which is capable of computing dense anatomical correspondences between two images at the voxel level.
Residual Aligner-based Network (RAN): Motion-separable structure for coarse-to-fine discontinuous deformable registration
jianqingzheng/res_aligner_net
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Medical Image Analysis 2023
Deformable image registration, the estimation of the spatial transformation between different images, is an important task in medical imaging.
