Share Email Print
cover

Proceedings Paper

A directional TV based ring artifact reduction method
Author(s): Morteza Salehjahromi; Qian Wang; Lars A. Gjesteby; Dan Harrison; Ge Wang; Hengyong Yu
Format Member Price Non-Member Price
PDF $17.00 $21.00

Paper Abstract

In computed tomography (CT), miscalibrated or imperfect detector elements produce stripe artifacts in the sinogram. The stripe artifacts in Radon space are responsible for concentric ring artifacts in the reconstructed images. To remove the ring artifacts from the images, there exist several methods. While most of the methods are performed in the image domain, a few of them are adopted in the projection or sinogram domain. In the latter methods, the sinogram is intended to be corrected before the image reconstruction. In this work, a novel optimization model is proposed to remove the ring artifacts in an iterative reconstruction procedure. To correct a sinogram, a new correcting vector is proposed to compensate for malfunctioning of detectors in the projection domain. Moreover, a novel directional total variation (DTV) based regularization is developed to penalize the ring artifacts in the image domain. The optimization problem is solved by using the alternating minimization scheme (AMS). In each iteration, the fidelity term along with the DTV-based regularization is first solved to find the image, and then the correcting coefficient vector is updated according to the obtained image. Because the sinogram and the image are simultaneously updated, the proposed method basically performs in both the image and sinogram domains. The proposed method is evaluated using real preclinical datasets containing strong ring artifacts , and the experimental results show that the proposed algorithm can efficiently suppress the ring artifacts.

Paper Details

Date Published: 1 March 2019
PDF: 7 pages
Proc. SPIE 10948, Medical Imaging 2019: Physics of Medical Imaging, 109482C (1 March 2019); doi: 10.1117/12.2513037
Show Author Affiliations
Morteza Salehjahromi, Univ. of Massachusetts Lowell (United States)
Qian Wang, Univ. of Massachusetts Lowell (United States)
Lars A. Gjesteby, Rensselaer Polytechnic Institute (United States)
Dan Harrison, Rensselaer Polytechnic Institute (United States)
Ge Wang, Rensselaer Polytechnic Institute (United States)
Hengyong Yu, Univ. of Massachusetts Lowell (United States)


Published in SPIE Proceedings Vol. 10948:
Medical Imaging 2019: Physics of Medical Imaging
Taly Gilat Schmidt; Guang-Hong Chen; Hilde Bosmans, Editor(s)

© SPIE. Terms of Use
Back to Top