Implementing Natural Image Quality Evaluator for Performance Indicator on Noise Artefacts Recovery in CT Scan

Gunawan, R; Tran, Y; Zheng, J; Nguyen, H; Chai, R

Implementing Natural Image Quality Evaluator for Performance Indicator on Noise Artefacts Recovery in CT Scan

Gunawan, R Tran, Y Zheng, J Nguyen, H Chai, R

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Publisher:: IEEE
Publication Type:: Conference Proceeding
Citation:: 2023 45th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), 2023, 2023, pp. 1-4
Issue Date:: 2023-12-11

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Field	Value	Language
dc.contributor.author	Gunawan, R
dc.contributor.author	Tran, Y
dc.contributor.author	Zheng, J
dc.contributor.author	Nguyen, H
dc.contributor.author	Chai, R https://orcid.org/0000-0002-1922-7024
dc.date	2023-07-24
dc.date.accessioned	2024-05-02T11:55:42Z
dc.date.available	2024-05-02T11:55:42Z
dc.date.issued	2023-12-11
dc.identifier.citation	2023 45th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), 2023, 2023, pp. 1-4
dc.identifier.isbn	9798350324471
dc.identifier.issn	2375-7477
dc.identifier.issn	2694-0604
dc.identifier.uri	http://hdl.handle.net/10453/178536
dc.description.abstract	The two most common evaluators for CT scan denoising are Peak Signal to Noise Ratio PSNR and Structural Similarity Index SSIM This paper offers an alternative evaluator by utilizing of Natural Image Quality Evaluator NIQE assessment to determine the performance of denoising work on noise artefact The noise artefact was obtained during the cancer screening process and had a particular noise density pattern across the image NIQE is one of the blind image assessments which rely on the measurable deviation of image patch as a reference it can determine the improved quality of denoising image Due to the method of comparison in NIQE the two parameters patch size and sharpness threshold will play an essential part in getting the score compared with the result from the other evaluators PSNR and SSIM
dc.format	Print
dc.language	en
dc.publisher	IEEE
dc.relation.ispartof	2023 45th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)
dc.relation.ispartof	2023 45th Annual International Conference of the IEEE Engineering in Medicine and Biology Society
dc.relation.isbasedon	10.1109/embc40787.2023.10340822
dc.rights	info:eu-repo/semantics/closedAccess
dc.subject.mesh	Algorithms
dc.subject.mesh	Artifacts
dc.subject.mesh	Tomography, X-Ray Computed
dc.subject.mesh	Tomography, X-Ray Computed
dc.subject.mesh	Artifacts
dc.subject.mesh	Algorithms
dc.subject.mesh	Algorithms
dc.subject.mesh	Artifacts
dc.subject.mesh	Tomography, X-Ray Computed
dc.title	Implementing Natural Image Quality Evaluator for Performance Indicator on Noise Artefacts Recovery in CT Scan
dc.type	Conference Proceeding
utslib.citation.volume	2023
utslib.location.activity	Sydney, Australia
pubs.organisational-group	University of Technology Sydney
pubs.organisational-group	University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	University of Technology Sydney/Faculty of Engineering and Information Technology/School of Electrical and Data Engineering
utslib.copyright.status	closed_access	*
dc.date.updated	2024-05-02T11:55:41Z
pubs.finish-date	2023-07-27
pubs.publication-status	Published
pubs.start-date	2023-07-24
pubs.volume	2023

Abstract:

The two most common evaluators for CT scan denoising are Peak Signal to Noise Ratio PSNR and Structural Similarity Index SSIM This paper offers an alternative evaluator by utilizing of Natural Image Quality Evaluator NIQE assessment to determine the performance of denoising work on noise artefact The noise artefact was obtained during the cancer screening process and had a particular noise density pattern across the image NIQE is one of the blind image assessments which rely on the measurable deviation of image patch as a reference it can determine the improved quality of denoising image Due to the method of comparison in NIQE the two parameters patch size and sharpness threshold will play an essential part in getting the score compared with the result from the other evaluators PSNR and SSIM

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http://hdl.handle.net/10453/178536