A metal artifact reduction algorithm in CT using multiple prior images by recursive active contour segmentation.

We propose a novel metal artifact reduction (MAR) algorithm for CT images that completes a corrupted sinogram along the metal trace region. When metal implants are located inside a field of view, they create a barrier to the transmitted X-ray beam due to the high attenuation of metals, which signifi...

Full description

Bibliographic Details
Main Authors: Haewon Nam, Jongduk Baek
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2017-01-01
Series:PLoS ONE
Online Access:http://europepmc.org/articles/PMC5467844?pdf=render
id doaj-1bce4d2c18df489ca26cc03248755e01
record_format Article
spelling doaj-1bce4d2c18df489ca26cc03248755e012020-11-25T00:40:18ZengPublic Library of Science (PLoS)PLoS ONE1932-62032017-01-01126e017902210.1371/journal.pone.0179022A metal artifact reduction algorithm in CT using multiple prior images by recursive active contour segmentation.Haewon NamJongduk BaekWe propose a novel metal artifact reduction (MAR) algorithm for CT images that completes a corrupted sinogram along the metal trace region. When metal implants are located inside a field of view, they create a barrier to the transmitted X-ray beam due to the high attenuation of metals, which significantly degrades the image quality. To fill in the metal trace region efficiently, the proposed algorithm uses multiple prior images with residual error compensation in sinogram space. Multiple prior images are generated by applying a recursive active contour (RAC) segmentation algorithm to the pre-corrected image acquired by MAR with linear interpolation, where the number of prior image is controlled by RAC depending on the object complexity. A sinogram basis is then acquired by forward projection of the prior images. The metal trace region of the original sinogram is replaced by the linearly combined sinogram of the prior images. Then, the additional correction in the metal trace region is performed to compensate the residual errors occurred by non-ideal data acquisition condition. The performance of the proposed MAR algorithm is compared with MAR with linear interpolation and the normalized MAR algorithm using simulated and experimental data. The results show that the proposed algorithm outperforms other MAR algorithms, especially when the object is complex with multiple bone objects.http://europepmc.org/articles/PMC5467844?pdf=render
collection DOAJ
language English
format Article
sources DOAJ
author Haewon Nam
Jongduk Baek
spellingShingle Haewon Nam
Jongduk Baek
A metal artifact reduction algorithm in CT using multiple prior images by recursive active contour segmentation.
PLoS ONE
author_facet Haewon Nam
Jongduk Baek
author_sort Haewon Nam
title A metal artifact reduction algorithm in CT using multiple prior images by recursive active contour segmentation.
title_short A metal artifact reduction algorithm in CT using multiple prior images by recursive active contour segmentation.
title_full A metal artifact reduction algorithm in CT using multiple prior images by recursive active contour segmentation.
title_fullStr A metal artifact reduction algorithm in CT using multiple prior images by recursive active contour segmentation.
title_full_unstemmed A metal artifact reduction algorithm in CT using multiple prior images by recursive active contour segmentation.
title_sort metal artifact reduction algorithm in ct using multiple prior images by recursive active contour segmentation.
publisher Public Library of Science (PLoS)
series PLoS ONE
issn 1932-6203
publishDate 2017-01-01
description We propose a novel metal artifact reduction (MAR) algorithm for CT images that completes a corrupted sinogram along the metal trace region. When metal implants are located inside a field of view, they create a barrier to the transmitted X-ray beam due to the high attenuation of metals, which significantly degrades the image quality. To fill in the metal trace region efficiently, the proposed algorithm uses multiple prior images with residual error compensation in sinogram space. Multiple prior images are generated by applying a recursive active contour (RAC) segmentation algorithm to the pre-corrected image acquired by MAR with linear interpolation, where the number of prior image is controlled by RAC depending on the object complexity. A sinogram basis is then acquired by forward projection of the prior images. The metal trace region of the original sinogram is replaced by the linearly combined sinogram of the prior images. Then, the additional correction in the metal trace region is performed to compensate the residual errors occurred by non-ideal data acquisition condition. The performance of the proposed MAR algorithm is compared with MAR with linear interpolation and the normalized MAR algorithm using simulated and experimental data. The results show that the proposed algorithm outperforms other MAR algorithms, especially when the object is complex with multiple bone objects.
url http://europepmc.org/articles/PMC5467844?pdf=render
work_keys_str_mv AT haewonnam ametalartifactreductionalgorithminctusingmultiplepriorimagesbyrecursiveactivecontoursegmentation
AT jongdukbaek ametalartifactreductionalgorithminctusingmultiplepriorimagesbyrecursiveactivecontoursegmentation
AT haewonnam metalartifactreductionalgorithminctusingmultiplepriorimagesbyrecursiveactivecontoursegmentation
AT jongdukbaek metalartifactreductionalgorithminctusingmultiplepriorimagesbyrecursiveactivecontoursegmentation
_version_ 1725291104531644416