Image Registration

124 papers with code • 2 benchmarks • 6 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 )


Use these libraries to find Image Registration models and implementations

Most implemented papers

VoxelMorph: A Learning Framework for Deformable Medical Image Registration

voxelmorph/voxelmorph 14 Sep 2018

In contrast to this approach, and building on recent learning-based methods, we formulate registration as a function that maps an input image pair to a deformation field that aligns these images.

Recursive Cascaded Networks for Unsupervised Medical Image Registration

microsoft/Recursive-Cascaded-Networks ICCV 2019

We present recursive cascaded networks, a general architecture that enables learning deep cascades, for deformable image registration.

Kornia: an Open Source Differentiable Computer Vision Library for PyTorch

kornia/kornia 5 Oct 2019

This work presents Kornia -- an open source computer vision library which consists of a set of differentiable routines and modules to solve generic computer vision problems.

Indirect Image Registration with Large Diffeomorphic Deformations

odlgroup/odl 13 Jun 2017

The paper adapts the large deformation diffeomorphic metric mapping framework for image registration to the indirect setting where a template is registered against a target that is given through indirect noisy observations.

An Unsupervised Learning Model for Deformable Medical Image Registration

balakg/voxelmorph CVPR 2018

We define registration as a parametric function, and optimize its parameters given a set of images from a collection of interest.

AirLab: Autograd Image Registration Laboratory

airlab-unibas/airlab 26 Jun 2018

With the "Autograd Image Registration Laboratory" (AIRLab), we introduce an open laboratory for image registration tasks, where the analytic gradients of the objective function are computed automatically and the device where the computations are performed, on a CPU or a GPU, is transparent.

Robustness via Retrying: Closed-Loop Robotic Manipulation with Self-Supervised Learning

febert/neuralproposal_cem_classproject 6 Oct 2018

We demonstrate that this idea can be combined with a video-prediction based controller to enable complex behaviors to be learned from scratch using only raw visual inputs, including grasping, repositioning objects, and non-prehensile manipulation.

MRI to CT Translation with GANs

bodokaiser/mrtoct-tensorflow 16 Jan 2019

We present a detailed description and reference implementation of preprocessing steps necessary to prepare the public Retrospective Image Registration Evaluation (RIRE) dataset for the task of magnetic resonance imaging (MRI) to X-ray computed tomography (CT) translation.

Large Deformation Diffeomorphic Image Registration with Laplacian Pyramid Networks

cwmok/LapIRN 29 Jun 2020

Deep learning-based methods have recently demonstrated promising results in deformable image registration for a wide range of medical image analysis tasks.