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Markov random field segmentation for industrial computed tomography with metal artefacts
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Jaiswal, Avinash, Williams, M. A., Bhalerao, Abhir, Tiwari, Manoj K. and Warnett, Jason M. (2018) Markov random field segmentation for industrial computed tomography with metal artefacts. Journal of X-ray science and technology, 26 (4). pp. 573-591. doi:10.3233/XST-17322 ISSN 1095-9114.
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WRAP-Markov-random-field-segmentation-computed-tomography-metal-Williams-2018.pdf - Published Version - Requires a PDF viewer. Available under License Creative Commons: Attribution-Noncommercial 4.0. Download (1275Kb) | Preview |
Official URL: http://doi.org/10.3233/XST-17322
Abstract
X-ray Computed Tomography (XCT) has become an important tool for industrial measurement and quality control through its ability to measure internal structures and volumetric defects. Segmentation of constituent materials in the volume acquired through XCT is one of the most critical factors that influence its robustness and repeatability. Highly attenuating materials such as steel can introduce artefacts in CT images that adversely affect the segmentation process, and results in large errors during quantification. This paper presents a Markov Random Field (MRF) segmentation method as a suitable approach for industrial samples with metal artefacts. The advantages of employing the MRF segmentation method are shown in comparison with Otsu thresholding on CT data from two industrial objects.
Item Type: | Journal Article | ||||||
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Subjects: | Q Science > QA Mathematics R Medicine > RC Internal medicine |
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Divisions: | Faculty of Science, Engineering and Medicine > Science > Computer Science Faculty of Science, Engineering and Medicine > Engineering > WMG (Formerly the Warwick Manufacturing Group) |
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SWORD Depositor: | Library Publications Router | ||||||
Library of Congress Subject Headings (LCSH): | Tomography -- Industrial applications, Markov random fields | ||||||
Journal or Publication Title: | Journal of X-ray science and technology | ||||||
Publisher: | IOS Press | ||||||
ISSN: | 1095-9114 | ||||||
Official Date: | 15 March 2018 | ||||||
Dates: |
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Volume: | 26 | ||||||
Number: | 4 | ||||||
Page Range: | pp. 573-591 | ||||||
DOI: | 10.3233/XST-17322 | ||||||
Status: | Peer Reviewed | ||||||
Publication Status: | Published | ||||||
Access rights to Published version: | Open Access (Creative Commons) | ||||||
Date of first compliant deposit: | 18 September 2018 | ||||||
Date of first compliant Open Access: | 18 September 2018 |
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