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Level-Set Method for Image Analysis of Schlemm's Canal and Trabecular Meshwork
PURPOSE: To evaluate different segmentation methods in analyzing Schlemm's canal (SC) and the trabecular meshwork (TM) in ultrasound biomicroscopy (UBM) images. METHODS: Twenty-six healthy volunteers were recruited. The intraocular pressure (IOP) was measured while study subjects blew a trumpet...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Association for Research in Vision and Ophthalmology
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7476667/ https://www.ncbi.nlm.nih.gov/pubmed/32953247 http://dx.doi.org/10.1167/tvst.9.10.7 |
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author | Wang, Xin Zhai, Yuxi Liu, Xueyan Zhu, Wei Gao, Jianlu |
author_facet | Wang, Xin Zhai, Yuxi Liu, Xueyan Zhu, Wei Gao, Jianlu |
author_sort | Wang, Xin |
collection | PubMed |
description | PURPOSE: To evaluate different segmentation methods in analyzing Schlemm's canal (SC) and the trabecular meshwork (TM) in ultrasound biomicroscopy (UBM) images. METHODS: Twenty-six healthy volunteers were recruited. The intraocular pressure (IOP) was measured while study subjects blew a trumpet. Images were obtained at different IOPs by 50-MHz UBM. ImageJ software and three segmentation methods—K-means, fuzzy C-means, and level set—were applied to segment the UBM images. The quantitative analysis of the TM-SC region was based on the segmentation results. The relative error and the interclass correlation coefficient (ICC) were used to quantify the accuracy and the repeatability of measurements. Pearson correlation analysis was conducted to evaluate the associations between the IOP and the TM and SC geometric measurements. RESULTS: A total of 104 UBM images were obtained. Among them, 84 were adequately clear to be segmented. The level-set method results had a higher similarity to ImageJ results than the other two methods. The ICC values of the level-set method were 0.97, 0.95, 0.9, and 0.57, respectively. Pearson correlation coefficients for the IOP to the SC area, SC perimeter, SC length, and TM width were −0.91, −0.72, −0.66, and −0.61 (P < 0.0001), respectively. CONCLUSIONS: The level-set method showed better accuracy than the other two methods. Compared with manual methods, it can achieve similar precision, better repeatability, and greater efficiency. Therefore, the level-set method can be used for reliable UBM image segmentation. TRANSLATIONAL RELEVANCE: The level-set method can be used to analyze TM and SC region in UBM images semiautomatically. |
format | Online Article Text |
id | pubmed-7476667 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | The Association for Research in Vision and Ophthalmology |
record_format | MEDLINE/PubMed |
spelling | pubmed-74766672020-09-18 Level-Set Method for Image Analysis of Schlemm's Canal and Trabecular Meshwork Wang, Xin Zhai, Yuxi Liu, Xueyan Zhu, Wei Gao, Jianlu Transl Vis Sci Technol Article PURPOSE: To evaluate different segmentation methods in analyzing Schlemm's canal (SC) and the trabecular meshwork (TM) in ultrasound biomicroscopy (UBM) images. METHODS: Twenty-six healthy volunteers were recruited. The intraocular pressure (IOP) was measured while study subjects blew a trumpet. Images were obtained at different IOPs by 50-MHz UBM. ImageJ software and three segmentation methods—K-means, fuzzy C-means, and level set—were applied to segment the UBM images. The quantitative analysis of the TM-SC region was based on the segmentation results. The relative error and the interclass correlation coefficient (ICC) were used to quantify the accuracy and the repeatability of measurements. Pearson correlation analysis was conducted to evaluate the associations between the IOP and the TM and SC geometric measurements. RESULTS: A total of 104 UBM images were obtained. Among them, 84 were adequately clear to be segmented. The level-set method results had a higher similarity to ImageJ results than the other two methods. The ICC values of the level-set method were 0.97, 0.95, 0.9, and 0.57, respectively. Pearson correlation coefficients for the IOP to the SC area, SC perimeter, SC length, and TM width were −0.91, −0.72, −0.66, and −0.61 (P < 0.0001), respectively. CONCLUSIONS: The level-set method showed better accuracy than the other two methods. Compared with manual methods, it can achieve similar precision, better repeatability, and greater efficiency. Therefore, the level-set method can be used for reliable UBM image segmentation. TRANSLATIONAL RELEVANCE: The level-set method can be used to analyze TM and SC region in UBM images semiautomatically. The Association for Research in Vision and Ophthalmology 2020-09-04 /pmc/articles/PMC7476667/ /pubmed/32953247 http://dx.doi.org/10.1167/tvst.9.10.7 Text en Copyright 2020 The Authors http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. |
spellingShingle | Article Wang, Xin Zhai, Yuxi Liu, Xueyan Zhu, Wei Gao, Jianlu Level-Set Method for Image Analysis of Schlemm's Canal and Trabecular Meshwork |
title | Level-Set Method for Image Analysis of Schlemm's Canal and Trabecular Meshwork |
title_full | Level-Set Method for Image Analysis of Schlemm's Canal and Trabecular Meshwork |
title_fullStr | Level-Set Method for Image Analysis of Schlemm's Canal and Trabecular Meshwork |
title_full_unstemmed | Level-Set Method for Image Analysis of Schlemm's Canal and Trabecular Meshwork |
title_short | Level-Set Method for Image Analysis of Schlemm's Canal and Trabecular Meshwork |
title_sort | level-set method for image analysis of schlemm's canal and trabecular meshwork |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7476667/ https://www.ncbi.nlm.nih.gov/pubmed/32953247 http://dx.doi.org/10.1167/tvst.9.10.7 |
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