TV-regularized CT Reconstruction and Metal Artifact Reduction Using Inequality Constraints with Preconditioning

10/08/2018
by   Clemens Schiffer, et al.
0

Total variation(TV) regularization is applied to X-Ray computed tomography(CT) in an effort to reduce metal artifacts. Tikhonov regularization with L^2 data fidelity term and total variation regularization is augmented in this novel model by inequality constraints on sinogram data affected by metal to model errors caused by metal. The formulated problem is discretized and solved using the Chambolle-Pock algorithm. Faster convergence is achieved using preconditioning in a Douglas-Rachford spitting method as well as Advanced Direction Method of Multipliers(ADMM). The methods are applied to real and synthetic data demonstrating feasibility of the model to reduce metal artifacts. Technical details of CT data used and its processing are given in the appendix.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
04/26/2014

Sinogram constrained TV-minimization for metal artifact reduction in CT

A new method for reducing metal artifacts in X-ray computed tomography (...
research
12/19/2017

Scale-Space Anisotropic Total Variation for Limited Angle Tomography

This paper addresses streak reduction in limited angle tomography. Altho...
research
02/18/2014

A convergence proof of the split Bregman method for regularized least-squares problems

The split Bregman (SB) method [T. Goldstein and S. Osher, SIAM J. Imagin...
research
01/07/2019

Graph- and finite element-based total variation models for the inverse problem in diffuse optical tomography

Total variation (TV) is a powerful regularization method that has been w...
research
04/23/2023

A complementary ℓ^1-TV reconstruction algorithm for limited data CT

In a variety of tomographic applications, data cannot be fully acquired,...
research
03/03/2018

An Improved Method of Total Variation Superiorization Applied to Reconstruction in Proton Computed Tomography

Previous work showed that total variation superiorization (TVS) improves...
research
08/10/2022

Haar Wavelets, Gradients and Approximate TV Regularization

We show how total variation regularization of images in arbitrary dimens...

Please sign up or login with your details

Forgot password? Click here to reset