Feasibility of the Quantitative Assessment Method for CT Quality Control in Phantom Image Evaluation
Computed tomography (CT) quality control (QC) is regularly performed with standard phantoms, to bar faulty equipment from medical use. Its accuracy may be improved by replacing qualitative methods based on good visual distinction with pixel value-based quantitative methods. We hypothesized that stat...
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doaj-050cf5535879477fa661fbbb157f21982021-04-16T23:00:32ZengMDPI AGApplied Sciences2076-34172021-04-01113570357010.3390/app11083570Feasibility of the Quantitative Assessment Method for CT Quality Control in Phantom Image EvaluationKi Baek Lee0Ki Chang Nam1Ji Sung Jang2Ho Chul Kim3Biomedical Engineering Research Center, Asan Institute for Life Sciences, Asan Medical Center, 88 Olympic-ro 43-gil, Songpa-gu, Seoul 05505, KoreaDepartment of Medical Engineering, Dongguk University College of Medicine, 32 Dongguk-ro, Goyang-si, Gyeonggi-do 10326, KoreaDepartment of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul 05505, KoreaDepartment of Radiological Science, Eulji University, 553 Sanseong-daero, Sujeong-gu, Seongnam-si, Gyeonggi-do 13135, KoreaComputed tomography (CT) quality control (QC) is regularly performed with standard phantoms, to bar faulty equipment from medical use. Its accuracy may be improved by replacing qualitative methods based on good visual distinction with pixel value-based quantitative methods. We hypothesized that statistical texture analysis (TA) that covers the entire phantom image would be a more appropriate tool. Therefore, our study devised a novel QC method based on the TA for contrast resolution (CR) and spatial resolution (SR) and proposed new, quantitative CT QC criteria. TA of CR and SR images on an American Association of Physicists in Medicine (AAPM) CT Performance Phantom were performed with nine CT scanner models. Six texture descriptors derived from first-order statistics of grayscale image histograms were analyzed. Principal component analysis was used to reveal descriptors with high utility. For CR evaluation, contrast and softness were the most accurate descriptors. For SR evaluation, contrast, softness, and skewness were the most useful descriptors. We propose the following ranges: contrast for CR, 29.5 ± 15%, for SR, 29 ± 10%; softness for CR, <0.015, for SR, <0.014; and skewness for SR, >−1.85. Our novel TA method may improve the assessment of CR and SR of AAPM phantom images.https://www.mdpi.com/2076-3417/11/8/3570computed tomographyquality controlcontrast resolutionspatial resolutiontexture analysis |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Ki Baek Lee Ki Chang Nam Ji Sung Jang Ho Chul Kim |
spellingShingle |
Ki Baek Lee Ki Chang Nam Ji Sung Jang Ho Chul Kim Feasibility of the Quantitative Assessment Method for CT Quality Control in Phantom Image Evaluation Applied Sciences computed tomography quality control contrast resolution spatial resolution texture analysis |
author_facet |
Ki Baek Lee Ki Chang Nam Ji Sung Jang Ho Chul Kim |
author_sort |
Ki Baek Lee |
title |
Feasibility of the Quantitative Assessment Method for CT Quality Control in Phantom Image Evaluation |
title_short |
Feasibility of the Quantitative Assessment Method for CT Quality Control in Phantom Image Evaluation |
title_full |
Feasibility of the Quantitative Assessment Method for CT Quality Control in Phantom Image Evaluation |
title_fullStr |
Feasibility of the Quantitative Assessment Method for CT Quality Control in Phantom Image Evaluation |
title_full_unstemmed |
Feasibility of the Quantitative Assessment Method for CT Quality Control in Phantom Image Evaluation |
title_sort |
feasibility of the quantitative assessment method for ct quality control in phantom image evaluation |
publisher |
MDPI AG |
series |
Applied Sciences |
issn |
2076-3417 |
publishDate |
2021-04-01 |
description |
Computed tomography (CT) quality control (QC) is regularly performed with standard phantoms, to bar faulty equipment from medical use. Its accuracy may be improved by replacing qualitative methods based on good visual distinction with pixel value-based quantitative methods. We hypothesized that statistical texture analysis (TA) that covers the entire phantom image would be a more appropriate tool. Therefore, our study devised a novel QC method based on the TA for contrast resolution (CR) and spatial resolution (SR) and proposed new, quantitative CT QC criteria. TA of CR and SR images on an American Association of Physicists in Medicine (AAPM) CT Performance Phantom were performed with nine CT scanner models. Six texture descriptors derived from first-order statistics of grayscale image histograms were analyzed. Principal component analysis was used to reveal descriptors with high utility. For CR evaluation, contrast and softness were the most accurate descriptors. For SR evaluation, contrast, softness, and skewness were the most useful descriptors. We propose the following ranges: contrast for CR, 29.5 ± 15%, for SR, 29 ± 10%; softness for CR, <0.015, for SR, <0.014; and skewness for SR, >−1.85. Our novel TA method may improve the assessment of CR and SR of AAPM phantom images. |
topic |
computed tomography quality control contrast resolution spatial resolution texture analysis |
url |
https://www.mdpi.com/2076-3417/11/8/3570 |
work_keys_str_mv |
AT kibaeklee feasibilityofthequantitativeassessmentmethodforctqualitycontrolinphantomimageevaluation AT kichangnam feasibilityofthequantitativeassessmentmethodforctqualitycontrolinphantomimageevaluation AT jisungjang feasibilityofthequantitativeassessmentmethodforctqualitycontrolinphantomimageevaluation AT hochulkim feasibilityofthequantitativeassessmentmethodforctqualitycontrolinphantomimageevaluation |
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1721524308941996032 |