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Proceedings Paper

CT metal artifact reduction using MR image patches
Author(s): Jonathan S. Nielsen; Jens M. Edmund; Koen Van Leemput
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Paper Abstract

Metal implants give rise to metal artifacts in computed tomography (CT) images, which may lead to diagnostic errors and erroneous CT number estimates when the CT is used for radiation therapy planning. Methods for reducing metal artifacts by exploiting the anatomical information provided by coregistered magnetic resonance (MR) images are of great potential value, but remain technically challenging due to the poor contrast between bone and air on the MR image. In this paper, we present a novel MR-based algorithm for automatic CT metal artifact reduction (MAR), referred to as kerMAR. It combines kernel regression on known CT value/MR patch pairs in the uncorrupted patient volume with a forward model of the artifact corrupted values to estimate CT replacement values. In contrast to pseudo-CT generation that builds on multi-patient modelling, the algorithm requires no MR intensity normalisation or atlas registration. Image results for 7 head-and-neck radiation therapy patients with T1-weighted images acquired in the same fixation as the RT planning CT suggest a potential for more complete MAR close to the metal implants than the oMAR algorithm (Philips) used clinically. Our results further show improved performance in air and bone regions as compared to other MR-based MAR algorithms. In addition, we experimented with using kerMAR to define a prior for iterative reconstruction with the maximum likelihood transmission reconstruction algorithm, however with no apparent improvements

Paper Details

Date Published: 9 March 2018
PDF: 10 pages
Proc. SPIE 10573, Medical Imaging 2018: Physics of Medical Imaging, 105730P (9 March 2018); doi: 10.1117/12.2293815
Show Author Affiliations
Jonathan S. Nielsen, Technical Univ. of Denmark (Denmark)
Gentofte and Herlev Hospital (Denmark)
Jens M. Edmund, Gentofte and Herlev Hospital (Denmark)
Niels Bohr Institute, Univ. of Copenhagen (Denmark)
Koen Van Leemput, Technical Univ. of Denmark (Denmark)
Massachusetts General Hospital, Harvard Medical School (United States)

Published in SPIE Proceedings Vol. 10573:
Medical Imaging 2018: Physics of Medical Imaging
Joseph Y. Lo; Taly Gilat Schmidt; Guang-Hong Chen, Editor(s)

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