Comparison of Choroidal Thickness Measurements Using Semiautomated and Manual Segmentation Methods
This study demonstrated that a semiautomated segmentation method could help inexperienced practitioners to obtain choroidal thickness as good as experienced practitioners. The purpose of this study was to compare choroidal thickness measurements obtained by semiautomated and manual segmentation meth...
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Published in | Optometry and vision science Vol. 97; no. 2; pp. 121 - 127 |
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Main Authors | , , , , , , |
Format | Journal Article |
Language | English |
Published |
United States
Lippincott Williams & Wilkins
01.02.2020
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Subjects | |
Online Access | Get full text |
ISSN | 1040-5488 1538-9235 1538-9235 |
DOI | 10.1097/OPX.0000000000001473 |
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Abstract | This study demonstrated that a semiautomated segmentation method could help inexperienced practitioners to obtain choroidal thickness as good as experienced practitioners.
The purpose of this study was to compare choroidal thickness measurements obtained by semiautomated and manual segmentation methods.
Optical coherence tomography images of 37 eyes from 37 healthy young subjects acquired by a spectral-domain optical coherence tomography device were reviewed retrospectively. Two naive examiners measured choroidal thickness using manual and semiautomated methods, whereas two experienced examiners used only the semiautomated method. The semiautomated method referred to a fully automated segmentation program customized based on MATLAB and followed manual verification. After highlighting the inner and outer choroidal boundaries through automated segmentation, examiners reviewed these boundaries in each B-scan and conducted manual revisions if segmentation errors occurred. After selecting points where correct boundary was located, the software used a spline fit to blend the corrected region with the rest of the boundary. All measurements were summarized in a 6-mm Early Treatment Diabetic Retinopathy Study grid. Operation time spent to complete retinal and choroidal segmentation on each eye was recorded. Between-examiner agreements, that is, intraclass correlation coefficient and coefficient of reproducibility (CoR), were calculated among four sets of semiautomated measurements, and within-examiner agreements were comparisons between manual and semiautomated results from the same naive examiners. Eyes with thin or thick choroids were also analyzed separately.
The between-examiner and within-examiner agreements were excellent with intraclass correlation coefficient of 0.976 or greater. Pairwise within-examiner CoRs ranged from 17.4 to 47.1 μm. Pairwise between-examiner CoRs were between 13.0 and 38.9 μm. Eyes with thin choroid had better agreements than those with thick choroids. On average, naive examiners saved 3 to 5 minutes per eye using the semiautomated method.
With the help of a dedicated software, inexperienced practitioners could obtain choroidal thickness measurements with accuracy similar to experienced practitioners. Processing time with the semiautomated method was also reduced. |
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AbstractList | This study demonstrated that a semiautomated segmentation method could help inexperienced practitioners to obtain choroidal thickness as good as experienced practitioners.SIGNIFICANCEThis study demonstrated that a semiautomated segmentation method could help inexperienced practitioners to obtain choroidal thickness as good as experienced practitioners.The purpose of this study was to compare choroidal thickness measurements obtained by semiautomated and manual segmentation methods.PURPOSEThe purpose of this study was to compare choroidal thickness measurements obtained by semiautomated and manual segmentation methods.Optical coherence tomography images of 37 eyes from 37 healthy young subjects acquired by a spectral-domain optical coherence tomography device were reviewed retrospectively. Two naive examiners measured choroidal thickness using manual and semiautomated methods, whereas two experienced examiners used only the semiautomated method. The semiautomated method referred to a fully automated segmentation program customized based on MATLAB and followed manual verification. After highlighting the inner and outer choroidal boundaries through automated segmentation, examiners reviewed these boundaries in each B-scan and conducted manual revisions if segmentation errors occurred. After selecting points where correct boundary was located, the software used a spline fit to blend the corrected region with the rest of the boundary. All measurements were summarized in a 6-mm Early Treatment Diabetic Retinopathy Study grid. Operation time spent to complete retinal and choroidal segmentation on each eye was recorded. Between-examiner agreements, that is, intraclass correlation coefficient and coefficient of reproducibility (CoR), were calculated among four sets of semiautomated measurements, and within-examiner agreements were comparisons between manual and semiautomated results from the same naive examiners. Eyes with thin or thick choroids were also analyzed separately.METHODSOptical coherence tomography images of 37 eyes from 37 healthy young subjects acquired by a spectral-domain optical coherence tomography device were reviewed retrospectively. Two naive examiners measured choroidal thickness using manual and semiautomated methods, whereas two experienced examiners used only the semiautomated method. The semiautomated method referred to a fully automated segmentation program customized based on MATLAB and followed manual verification. After highlighting the inner and outer choroidal boundaries through automated segmentation, examiners reviewed these boundaries in each B-scan and conducted manual revisions if segmentation errors occurred. After selecting points where correct boundary was located, the software used a spline fit to blend the corrected region with the rest of the boundary. All measurements were summarized in a 6-mm Early Treatment Diabetic Retinopathy Study grid. Operation time spent to complete retinal and choroidal segmentation on each eye was recorded. Between-examiner agreements, that is, intraclass correlation coefficient and coefficient of reproducibility (CoR), were calculated among four sets of semiautomated measurements, and within-examiner agreements were comparisons between manual and semiautomated results from the same naive examiners. Eyes with thin or thick choroids were also analyzed separately.The between-examiner and within-examiner agreements were excellent with intraclass correlation coefficient of 0.976 or greater. Pairwise within-examiner CoRs ranged from 17.4 to 47.1 μm. Pairwise between-examiner CoRs were between 13.0 and 38.9 μm. Eyes with thin choroid had better agreements than those with thick choroids. On average, naive examiners saved 3 to 5 minutes per eye using the semiautomated method.RESULTSThe between-examiner and within-examiner agreements were excellent with intraclass correlation coefficient of 0.976 or greater. Pairwise within-examiner CoRs ranged from 17.4 to 47.1 μm. Pairwise between-examiner CoRs were between 13.0 and 38.9 μm. Eyes with thin choroid had better agreements than those with thick choroids. On average, naive examiners saved 3 to 5 minutes per eye using the semiautomated method.With the help of a dedicated software, inexperienced practitioners could obtain choroidal thickness measurements with accuracy similar to experienced practitioners. Processing time with the semiautomated method was also reduced.CONCLUSIONSWith the help of a dedicated software, inexperienced practitioners could obtain choroidal thickness measurements with accuracy similar to experienced practitioners. Processing time with the semiautomated method was also reduced. This study demonstrated that a semiautomated segmentation method could help inexperienced practitioners to obtain choroidal thickness as good as experienced practitioners. The purpose of this study was to compare choroidal thickness measurements obtained by semiautomated and manual segmentation methods. Optical coherence tomography images of 37 eyes from 37 healthy young subjects acquired by a spectral-domain optical coherence tomography device were reviewed retrospectively. Two naive examiners measured choroidal thickness using manual and semiautomated methods, whereas two experienced examiners used only the semiautomated method. The semiautomated method referred to a fully automated segmentation program customized based on MATLAB and followed manual verification. After highlighting the inner and outer choroidal boundaries through automated segmentation, examiners reviewed these boundaries in each B-scan and conducted manual revisions if segmentation errors occurred. After selecting points where correct boundary was located, the software used a spline fit to blend the corrected region with the rest of the boundary. All measurements were summarized in a 6-mm Early Treatment Diabetic Retinopathy Study grid. Operation time spent to complete retinal and choroidal segmentation on each eye was recorded. Between-examiner agreements, that is, intraclass correlation coefficient and coefficient of reproducibility (CoR), were calculated among four sets of semiautomated measurements, and within-examiner agreements were comparisons between manual and semiautomated results from the same naive examiners. Eyes with thin or thick choroids were also analyzed separately. The between-examiner and within-examiner agreements were excellent with intraclass correlation coefficient of 0.976 or greater. Pairwise within-examiner CoRs ranged from 17.4 to 47.1 μm. Pairwise between-examiner CoRs were between 13.0 and 38.9 μm. Eyes with thin choroid had better agreements than those with thick choroids. On average, naive examiners saved 3 to 5 minutes per eye using the semiautomated method. With the help of a dedicated software, inexperienced practitioners could obtain choroidal thickness measurements with accuracy similar to experienced practitioners. Processing time with the semiautomated method was also reduced. |
Author | Yu, Wing-Yan Lam, Andrew K. C. Alonso-Caneiro, David Wong, Ho-Yin Cheong, Allen M. Y. Zhao, Mei Lee, Roger |
AuthorAffiliation | Contact Lens and Visual Optics Laboratory, School of Optometry and Vision Science, Queensland University of Technology, Brisbane, Queensland, Australia Centre for Myopia Research, School of Optometry, The Hong Kong Polytechnic University, Hong Kong, China |
AuthorAffiliation_xml | – name: Centre for Myopia Research, School of Optometry, The Hong Kong Polytechnic University, Hong Kong, China – name: Contact Lens and Visual Optics Laboratory, School of Optometry and Vision Science, Queensland University of Technology, Brisbane, Queensland, Australia |
Author_xml | – sequence: 1 givenname: Mei surname: Zhao fullname: Zhao, Mei organization: Centre for Myopia Research, School of Optometry, The Hong Kong Polytechnic University, Hong Kong, China – sequence: 2 givenname: David surname: Alonso-Caneiro fullname: Alonso-Caneiro, David organization: Contact Lens and Visual Optics Laboratory, School of Optometry and Vision Science, Queensland University of Technology, Brisbane, Queensland, Australia – sequence: 3 givenname: Roger surname: Lee fullname: Lee, Roger organization: Centre for Myopia Research, School of Optometry, The Hong Kong Polytechnic University, Hong Kong, China – sequence: 4 givenname: Allen M. Y. surname: Cheong fullname: Cheong, Allen M. Y. organization: Centre for Myopia Research, School of Optometry, The Hong Kong Polytechnic University, Hong Kong, China – sequence: 5 givenname: Wing-Yan surname: Yu fullname: Yu, Wing-Yan organization: Centre for Myopia Research, School of Optometry, The Hong Kong Polytechnic University, Hong Kong, China – sequence: 6 givenname: Ho-Yin surname: Wong fullname: Wong, Ho-Yin organization: Centre for Myopia Research, School of Optometry, The Hong Kong Polytechnic University, Hong Kong, China – sequence: 7 givenname: Andrew K. C. surname: Lam fullname: Lam, Andrew K. C. |
BackLink | https://www.ncbi.nlm.nih.gov/pubmed/32011585$$D View this record in MEDLINE/PubMed |
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CitedBy_id | crossref_primary_10_3390_ijerph20043121 crossref_primary_10_1167_iovs_66_3_21 crossref_primary_10_1556_004_2021_00040 crossref_primary_10_3390_ph14111140 crossref_primary_10_3390_jcm11206169 crossref_primary_10_1038_s41433_023_02383_5 crossref_primary_10_1159_000541572 crossref_primary_10_1136_bjophthalmol_2021_318782 |
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Snippet | This study demonstrated that a semiautomated segmentation method could help inexperienced practitioners to obtain choroidal thickness as good as experienced... |
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SubjectTerms | Adult Choroid - anatomy & histology Choroid - diagnostic imaging Female Healthy Volunteers Humans Male Organ Size Reproducibility of Results Retrospective Studies Tomography, Optical Coherence - methods Young Adult |
Title | Comparison of Choroidal Thickness Measurements Using Semiautomated and Manual Segmentation Methods |
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