Automated artefact elimination in computed tomography: A preliminary report for traumatic brain injury and stroke

Dae Hyeon Park; Hakseung Kim; Young Tak Kim; Xiao Ke Yang; Hack Jin Lee; Eun Jin Jeong; Dong Ju Kim

doi:10.1109/IWW-BCI.2015.7073038

Automated artefact elimination in computed tomography: A preliminary report for traumatic brain injury and stroke

Dae Hyeon Park, Hakseung Kim, Young Tak Kim, Xiao Ke Yang, Hack Jin Lee, Eun Jin Jeong, Dong Ju Kim

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

1 Citation (Scopus)

Abstract

Traumatic brain injury (TBI) and stroke are the two major form of Acquired brain injury (ABI). To the effectiveness of the quantitative CT analysis in ABI, fully automated artefact elimination technique would be required. So, this study purpose to test the effectiveness of proposed algorithm against CT images from TBI and stroke patients. For the effectiveness of automated artefact elimination algorithm, CT images from stroke and TBI subjects were used, 522 and 240 respectively. As a result, the algorithm showed 100% success rate in eliminating artefacts by using 'fracture-sealing' algorithm. This algorithm was able to eliminate artefacts in CT image with acceptable failure rate. The fracture-sealing algorithm by utilizing pseudo-object pixels can be also useful for designating ROI, and for the automated artifact elimination.

Original language	English
Title of host publication	3rd International Winter Conference on Brain-Computer Interface, BCI 2015
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Print)	9781479974948
DOIs	https://doi.org/10.1109/IWW-BCI.2015.7073038
Publication status	Published - 2015 Mar 30
Event	2015 3rd International Winter Conference on Brain-Computer Interface, BCI 2015 - Gangwon-Do, Korea, Republic of Duration: 2015 Jan 12 → 2015 Jan 14

Other

Other	2015 3rd International Winter Conference on Brain-Computer Interface, BCI 2015
Country/Territory	Korea, Republic of
City	Gangwon-Do
Period	15/1/12 → 15/1/14

Keywords

Artefact Removing Algorithm
Computed tomography
Quntitatve CT analysis
Stroke
Traumatic brain injury

ASJC Scopus subject areas

Human-Computer Interaction
Cognitive Neuroscience
Sensory Systems

Access to Document

10.1109/IWW-BCI.2015.7073038

Cite this

Park, D. H., Kim, H., Kim, Y. T., Ke Yang, X., Lee, H. J., Jeong, E. J., & Kim, D. J. (2015). Automated artefact elimination in computed tomography: A preliminary report for traumatic brain injury and stroke. In 3rd International Winter Conference on Brain-Computer Interface, BCI 2015 [7073038] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IWW-BCI.2015.7073038

Automated artefact elimination in computed tomography: A preliminary report for traumatic brain injury and stroke. / Park, Dae Hyeon; Kim, Hakseung; Kim, Young Tak et al.
3rd International Winter Conference on Brain-Computer Interface, BCI 2015. Institute of Electrical and Electronics Engineers Inc., 2015. 7073038.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Park, DH, Kim, H, Kim, YT, Ke Yang, X, Lee, HJ, Jeong, EJ & Kim, DJ 2015, Automated artefact elimination in computed tomography: A preliminary report for traumatic brain injury and stroke. in 3rd International Winter Conference on Brain-Computer Interface, BCI 2015., 7073038, Institute of Electrical and Electronics Engineers Inc., 2015 3rd International Winter Conference on Brain-Computer Interface, BCI 2015, Gangwon-Do, Korea, Republic of, 15/1/12. https://doi.org/10.1109/IWW-BCI.2015.7073038

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abstract = "Traumatic brain injury (TBI) and stroke are the two major form of Acquired brain injury (ABI). To the effectiveness of the quantitative CT analysis in ABI, fully automated artefact elimination technique would be required. So, this study purpose to test the effectiveness of proposed algorithm against CT images from TBI and stroke patients. For the effectiveness of automated artefact elimination algorithm, CT images from stroke and TBI subjects were used, 522 and 240 respectively. As a result, the algorithm showed 100% success rate in eliminating artefacts by using 'fracture-sealing' algorithm. This algorithm was able to eliminate artefacts in CT image with acceptable failure rate. The fracture-sealing algorithm by utilizing pseudo-object pixels can be also useful for designating ROI, and for the automated artifact elimination.",

keywords = "Artefact Removing Algorithm, Computed tomography, Quntitatve CT analysis, Stroke, Traumatic brain injury",

author = "Park, {Dae Hyeon} and Hakseung Kim and Kim, {Young Tak} and {Ke Yang}, Xiao and Lee, {Hack Jin} and Jeong, {Eun Jin} and Kim, {Dong Ju}",

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AU - Park, Dae Hyeon

AU - Kim, Hakseung

AU - Kim, Young Tak

AU - Ke Yang, Xiao

AU - Lee, Hack Jin

AU - Jeong, Eun Jin

AU - Kim, Dong Ju

PY - 2015/3/30

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N2 - Traumatic brain injury (TBI) and stroke are the two major form of Acquired brain injury (ABI). To the effectiveness of the quantitative CT analysis in ABI, fully automated artefact elimination technique would be required. So, this study purpose to test the effectiveness of proposed algorithm against CT images from TBI and stroke patients. For the effectiveness of automated artefact elimination algorithm, CT images from stroke and TBI subjects were used, 522 and 240 respectively. As a result, the algorithm showed 100% success rate in eliminating artefacts by using 'fracture-sealing' algorithm. This algorithm was able to eliminate artefacts in CT image with acceptable failure rate. The fracture-sealing algorithm by utilizing pseudo-object pixels can be also useful for designating ROI, and for the automated artifact elimination.

AB - Traumatic brain injury (TBI) and stroke are the two major form of Acquired brain injury (ABI). To the effectiveness of the quantitative CT analysis in ABI, fully automated artefact elimination technique would be required. So, this study purpose to test the effectiveness of proposed algorithm against CT images from TBI and stroke patients. For the effectiveness of automated artefact elimination algorithm, CT images from stroke and TBI subjects were used, 522 and 240 respectively. As a result, the algorithm showed 100% success rate in eliminating artefacts by using 'fracture-sealing' algorithm. This algorithm was able to eliminate artefacts in CT image with acceptable failure rate. The fracture-sealing algorithm by utilizing pseudo-object pixels can be also useful for designating ROI, and for the automated artifact elimination.

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KW - Quntitatve CT analysis

KW - Stroke

KW - Traumatic brain injury

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Automated artefact elimination in computed tomography: A preliminary report for traumatic brain injury and stroke

Abstract

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Keywords

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