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Three-dimensional soft tissue landmark detection with marching cube algorithm

Current method of analyzing three-dimensional soft tissue data, especially in the frontal view, is subjective and has poor reliability. To overcome this limitation, the present study aimed to introduce a new method of analyzing soft tissue data reconstructed by marching cube algorithm (Program S) an...

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Autores principales: Lee, Yoonjung, Lee, Ji-Min, Park, Sun-Hyung, Choi, Yoon Jeong, Choi, Sung-Hwan, Hwang, Jae Joon, Yu, Hyung-Seog
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9883223/
https://www.ncbi.nlm.nih.gov/pubmed/36707701
http://dx.doi.org/10.1038/s41598-023-28792-w
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author Lee, Yoonjung
Lee, Ji-Min
Park, Sun-Hyung
Choi, Yoon Jeong
Choi, Sung-Hwan
Hwang, Jae Joon
Yu, Hyung-Seog
author_facet Lee, Yoonjung
Lee, Ji-Min
Park, Sun-Hyung
Choi, Yoon Jeong
Choi, Sung-Hwan
Hwang, Jae Joon
Yu, Hyung-Seog
author_sort Lee, Yoonjung
collection PubMed
description Current method of analyzing three-dimensional soft tissue data, especially in the frontal view, is subjective and has poor reliability. To overcome this limitation, the present study aimed to introduce a new method of analyzing soft tissue data reconstructed by marching cube algorithm (Program S) and compare it with a commercially available program (Program A). Cone-beam computed tomography images of 42 patients were included. Two orthodontists digitized six landmarks (pronasale, columella, upper and lower lip, right and left cheek) twice using both programs in two-week intervals, and the reliability was compared. Furthermore, computer-calculated point (CC point) was developed to evaluate whether human error could be reduced. The results showed that the intra- and inter-examiner reliability of Program S (99.7–100% and 99.9–100%, respectively) were higher than that of Program A (64.0–99.9% and 76.1–99.9%, respectively). Moreover, the inter-examiner difference of coordinate values and distances for all six landmarks in Program S was lower than Program A. Lastly, CC point was provided as a consistent single point. Therefore, it was validated that this new methodology can increase the intra- and inter-examiner reliability of soft tissue landmark digitation and CC point can be used as a landmark to reduce human error.
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spelling pubmed-98832232023-01-29 Three-dimensional soft tissue landmark detection with marching cube algorithm Lee, Yoonjung Lee, Ji-Min Park, Sun-Hyung Choi, Yoon Jeong Choi, Sung-Hwan Hwang, Jae Joon Yu, Hyung-Seog Sci Rep Article Current method of analyzing three-dimensional soft tissue data, especially in the frontal view, is subjective and has poor reliability. To overcome this limitation, the present study aimed to introduce a new method of analyzing soft tissue data reconstructed by marching cube algorithm (Program S) and compare it with a commercially available program (Program A). Cone-beam computed tomography images of 42 patients were included. Two orthodontists digitized six landmarks (pronasale, columella, upper and lower lip, right and left cheek) twice using both programs in two-week intervals, and the reliability was compared. Furthermore, computer-calculated point (CC point) was developed to evaluate whether human error could be reduced. The results showed that the intra- and inter-examiner reliability of Program S (99.7–100% and 99.9–100%, respectively) were higher than that of Program A (64.0–99.9% and 76.1–99.9%, respectively). Moreover, the inter-examiner difference of coordinate values and distances for all six landmarks in Program S was lower than Program A. Lastly, CC point was provided as a consistent single point. Therefore, it was validated that this new methodology can increase the intra- and inter-examiner reliability of soft tissue landmark digitation and CC point can be used as a landmark to reduce human error. Nature Publishing Group UK 2023-01-27 /pmc/articles/PMC9883223/ /pubmed/36707701 http://dx.doi.org/10.1038/s41598-023-28792-w Text en © The Author(s) 2023, corrected publication 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Lee, Yoonjung
Lee, Ji-Min
Park, Sun-Hyung
Choi, Yoon Jeong
Choi, Sung-Hwan
Hwang, Jae Joon
Yu, Hyung-Seog
Three-dimensional soft tissue landmark detection with marching cube algorithm
title Three-dimensional soft tissue landmark detection with marching cube algorithm
title_full Three-dimensional soft tissue landmark detection with marching cube algorithm
title_fullStr Three-dimensional soft tissue landmark detection with marching cube algorithm
title_full_unstemmed Three-dimensional soft tissue landmark detection with marching cube algorithm
title_short Three-dimensional soft tissue landmark detection with marching cube algorithm
title_sort three-dimensional soft tissue landmark detection with marching cube algorithm
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9883223/
https://www.ncbi.nlm.nih.gov/pubmed/36707701
http://dx.doi.org/10.1038/s41598-023-28792-w
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