Metal artifact reduction based on automated sinogram segmentation and adaptive multiresolution MAP reconstruction method

Defne Us, Erman Acar, Ulla Ruotsalainen

Research output: Chapter in Book / Report / Conference proceedingConference contributionAcademicpeer-review

Abstract

High density objects in the field of view (FOV) cause artifacts in medical imaging. In X-ray computed tomography (CT), there are several ways to eliminate the effects of these artifacts. This paper aims to evaluate the performance of a novel reconstruction algorithm which accurately segments the metallic regions and reconstruct sharp metal/tissue boundaries, while reducing the artifacts around the metallic regions. This algorithm uses a multilevel segmentation algorithm based on Otsu's threshold and adaptive multiresolution maximum a-posteriori expectation maximization (amMAP-EM). The qualities of Gaussian noise contaminated images were evaluated quantitatively using mean squared error and line profile analysis. The reconstructed image were compared with filtered backprojection (FBP) and maximum likelihood expectation maximization (MLEM) methods. According to the results, it is possible to reconstruct the images with more clear and sharper metal/tissue boundaries using amMAP-EM compared to MLEM and FBP, while avoiding the undesired artifacts such as blurring, streak artifacts or ringing.

Original languageEnglish
Title of host publication2015 IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS/MIC 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781467398626
DOIs
Publication statusPublished - 3 Oct 2016
Externally publishedYes
Event2015 IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS/MIC 2015 - San Diego, United States
Duration: 31 Oct 20157 Nov 2015

Publication series

Name2015 IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS/MIC 2015

Conference

Conference2015 IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS/MIC 2015
CountryUnited States
CitySan Diego
Period31/10/157/11/15

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Us, D., Acar, E., & Ruotsalainen, U. (2016). Metal artifact reduction based on automated sinogram segmentation and adaptive multiresolution MAP reconstruction method. In 2015 IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS/MIC 2015 [7582104] (2015 IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS/MIC 2015). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/NSSMIC.2015.7582104