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Effect of surface-partial-volume correction and adaptive threshold on segmentation of uroliths in computed tomography

Computed tomography (CT) is used to diagnose urolithiasis, a prevalent condition. In order to establish the strongest foundation for the quantifiability of urolithiasis, this study aims to develop semi-automated urolithiasis segmentation methods for CT images that differ in terms of surface-partial-...

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Autores principales: Neubauer, Jakob, Wilhelm, Konrad, Gratzke, Christian, Bamberg, Fabian, Reisert, Marco, Kellner, Elias
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10289361/
https://www.ncbi.nlm.nih.gov/pubmed/37352326
http://dx.doi.org/10.1371/journal.pone.0286016
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author Neubauer, Jakob
Wilhelm, Konrad
Gratzke, Christian
Bamberg, Fabian
Reisert, Marco
Kellner, Elias
author_facet Neubauer, Jakob
Wilhelm, Konrad
Gratzke, Christian
Bamberg, Fabian
Reisert, Marco
Kellner, Elias
author_sort Neubauer, Jakob
collection PubMed
description Computed tomography (CT) is used to diagnose urolithiasis, a prevalent condition. In order to establish the strongest foundation for the quantifiability of urolithiasis, this study aims to develop semi-automated urolithiasis segmentation methods for CT images that differ in terms of surface-partial-volume correction and adaptive thresholding. It also examines the diagnostic accuracy of these methods in terms of volume and maximum stone diameter. One hundred and one uroliths were positioned in an anthropomorphic phantom and prospectively examined in CT. Four different segmentation methods were developed and used to segment the uroliths semi-automatically based on CT images. Volume and maximum diameter were calculated from the segmentations. Volume and maximum diameter of the uroliths were measured independently by three urologists by means of electronic calipers. The average value of the urologists´ measurements was used as a reference standard. Statistical analysis was performed with multivariate Bartlett’s test. Volume and maximum diameter were in very good agreement with the reference measurements (r>0.99) and the diagnostic accuracy of all segmentation methods used was very high. Regarding the diagnostic accuracy no difference could be detected between the different segmentation methods tested (p>0.55). All four segmentation methods allow for accurate characterization of urolithiasis in CT with respect to volume and maximum diameter of uroliths. Thus, a simple thresholding approach with an absolute value may suffice for robust determination of volume and maximum diameter in urolithiasis.
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spelling pubmed-102893612023-06-24 Effect of surface-partial-volume correction and adaptive threshold on segmentation of uroliths in computed tomography Neubauer, Jakob Wilhelm, Konrad Gratzke, Christian Bamberg, Fabian Reisert, Marco Kellner, Elias PLoS One Research Article Computed tomography (CT) is used to diagnose urolithiasis, a prevalent condition. In order to establish the strongest foundation for the quantifiability of urolithiasis, this study aims to develop semi-automated urolithiasis segmentation methods for CT images that differ in terms of surface-partial-volume correction and adaptive thresholding. It also examines the diagnostic accuracy of these methods in terms of volume and maximum stone diameter. One hundred and one uroliths were positioned in an anthropomorphic phantom and prospectively examined in CT. Four different segmentation methods were developed and used to segment the uroliths semi-automatically based on CT images. Volume and maximum diameter were calculated from the segmentations. Volume and maximum diameter of the uroliths were measured independently by three urologists by means of electronic calipers. The average value of the urologists´ measurements was used as a reference standard. Statistical analysis was performed with multivariate Bartlett’s test. Volume and maximum diameter were in very good agreement with the reference measurements (r>0.99) and the diagnostic accuracy of all segmentation methods used was very high. Regarding the diagnostic accuracy no difference could be detected between the different segmentation methods tested (p>0.55). All four segmentation methods allow for accurate characterization of urolithiasis in CT with respect to volume and maximum diameter of uroliths. Thus, a simple thresholding approach with an absolute value may suffice for robust determination of volume and maximum diameter in urolithiasis. Public Library of Science 2023-06-23 /pmc/articles/PMC10289361/ /pubmed/37352326 http://dx.doi.org/10.1371/journal.pone.0286016 Text en © 2023 Neubauer et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Neubauer, Jakob
Wilhelm, Konrad
Gratzke, Christian
Bamberg, Fabian
Reisert, Marco
Kellner, Elias
Effect of surface-partial-volume correction and adaptive threshold on segmentation of uroliths in computed tomography
title Effect of surface-partial-volume correction and adaptive threshold on segmentation of uroliths in computed tomography
title_full Effect of surface-partial-volume correction and adaptive threshold on segmentation of uroliths in computed tomography
title_fullStr Effect of surface-partial-volume correction and adaptive threshold on segmentation of uroliths in computed tomography
title_full_unstemmed Effect of surface-partial-volume correction and adaptive threshold on segmentation of uroliths in computed tomography
title_short Effect of surface-partial-volume correction and adaptive threshold on segmentation of uroliths in computed tomography
title_sort effect of surface-partial-volume correction and adaptive threshold on segmentation of uroliths in computed tomography
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10289361/
https://www.ncbi.nlm.nih.gov/pubmed/37352326
http://dx.doi.org/10.1371/journal.pone.0286016
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