Image Registration
235 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
| Trend | Dataset | Best Model | Paper | Code | Compare |
|---|---|---|---|---|---|
|
|||||
|
|||||
|
|||||
|
|||||
|
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 with no code
Low Rank Groupwise Deformations for Motion Tracking in Cardiac Cine MRI
Diffeomorphic image registration is a commonly used method to deform one image to resemble another.
Innovative Quantitative Analysis for Disease Progression Assessment in Familial Cerebral Cavernous Malformations
To alleviate this problem, we propose a quantitative statistical framework for FCCM, comprising an efficient annotation module, an FCCM lesion segmentation module, and an FCCM lesion quantitative statistics module.
EfficientMorph: Parameter-Efficient Transformer-Based Architecture for 3D Image Registration
Secondly, feature similarities across attention heads that were recently found in multi-head attention architectures indicate a significant computational redundancy, suggesting that the capacity of the network could be better utilized to enhance performance.
A Spectrum-based Image Denoising Method with Edge Feature Enhancement
Image denoising stands as a critical challenge in image processing and computer vision, aiming to restore the original image from noise-affected versions caused by various intrinsic and extrinsic factors.
UDCR: Unsupervised Aortic DSA/CTA Rigid Registration Using Deep Reinforcement Learning and Overlap Degree Calculation
In this paper, we propose an unsupervised method, UDCR, for aortic DSA/CTA rigid registration based on deep reinforcement learning.
From Registration Uncertainty to Segmentation Uncertainty
Here, we propose a novel framework to concurrently estimate both the epistemic and aleatoric segmentation uncertainties for image registration.
Coronary artery segmentation in non-contrast calcium scoring CT images using deep learning
In this paper, we address this research gap and introduce a deep learning algorithm for segmenting coronary arteries in multi-vendor ECG-gated non-contrast cardiac CT images which benefits from a novel framework for semi-automatic generation of Ground Truth (GT) via image registration.
Modality-Agnostic Structural Image Representation Learning for Deformable Multi-Modality Medical Image Registration
Existing multi-modality image registration algorithms rely on statistical-based similarity measures or local structural image representations.
Multimodal Learning To Improve Cardiac Late Mechanical Activation Detection From Cine MR Images
This paper presents a multimodal deep learning framework that utilizes advanced image techniques to improve the performance of clinical analysis heavily dependent on routinely acquired standard images.
General Purpose Image Encoder DINOv2 for Medical Image Registration
In this paper, we present a training-free deformable image registration method, DINO-Reg, leveraging a general purpose image encoder DINOv2 for image feature extraction.
