Image Registration
236 papers with code • 5 benchmarks • 11 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
Most implemented papers
GLAMpoints: Greedily Learned Accurate Match points
PruneTruong/GLAMpoints_pytorch
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ICCV 2019
We introduce a novel CNN-based feature point detector - GLAMpoints - learned in a semi-supervised manner.
Large Deformation Diffeomorphic Image Registration with Laplacian Pyramid Networks
cwmok/LapIRN
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Deep learning-based methods have recently demonstrated promising results in deformable image registration for a wide range of medical image analysis tasks.
D-Net: Siamese based Network with Mutual Attention for Volume Alignment
code-implementation1/Code1
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Alignment of contrast and non-contrast-enhanced imaging is essential for the quantification of changes in several biomedical applications.
Conditional Deformable Image Registration with Convolutional Neural Network
cwmok/LapIRN
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In this paper, we propose a conditional image registration method and a new self-supervised learning paradigm for deep deformable image registration.
Distinctive Image Features from Scale-Invariant Keypoints
kornia/kornia
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This paper presents a method for extracting distinctive invariant features from images that can be used to perform reliable matching between different views of an object or scene.
Repeatability of Multiparametric Prostate MRI Radiomics Features
In this study we assessed the repeatability of the values of radiomics features for small prostate tumors using test-retest Multiparametric Magnetic Resonance Imaging (mpMRI) images.
Fast and Robust Symmetric Image Registration Based on Distances Combining Intensity and Spatial Information
The method exhibits greater robustness and higher accuracy than similarity measures in common use, when inserted into a standard gradient-based registration framework available as part of the open source Insight Segmentation and Registration Toolkit (ITK).
Inverse-Consistent Deep Networks for Unsupervised Deformable Image Registration
Deformable image registration is a fundamental task in medical image analysis, aiming to establish a dense and non-linear correspondence between a pair of images.
Fast Graph-Cut Based Optimization for Practical Dense Deformable Registration of Volume Images
Objective: Deformable image registration is a fundamental problem in medical image analysis, with applications such as longitudinal studies, population modeling, and atlas based image segmentation.
Networks for Joint Affine and Non-parametric Image Registration
uncbiag/registration
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CVPR 2019
In contrast to existing approaches, our framework combines two registration methods: an affine registration and a vector momentum-parameterized stationary velocity field (vSVF) model.
