Automated Mathematical Algorithm for Quantitative Measurement of Strabismus Based on Photographs of Nine Cardinal Gaze Positions
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Kang, Yena Christina | - |
dc.contributor.author | Yang, Hee Kyung | - |
dc.contributor.author | Kim, Young Jae | - |
dc.contributor.author | Hwang, Jeong-Min | - |
dc.contributor.author | Kim, Kwang Gi | - |
dc.date.accessioned | 2024-01-01T03:30:19Z | - |
dc.date.available | 2024-01-01T03:30:19Z | - |
dc.date.issued | 2022-03 | - |
dc.identifier.issn | 2314-6133 | - |
dc.identifier.issn | 2314-6141 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/gachon/handle/2020.sw.gachon/89878 | - |
dc.description.abstract | This study presents an automated algorithm that measures ocular deviation quantitatively using photographs of the nine cardinal points of gaze by means of deep learning (DL) and image processing techniques. Photographs were collected from patients with strabismus. The images were used as inputs for the DL segmentation models that segmented the sclerae and limbi. Subsequently, the images were registered for the mathematical algorithm. Two-dimensional sclera and limbus were modeled, and the corneal light reflex points of the primary gaze images were determined. Limbus recognition was performed to measure the pixel-wise distance between the corneal reflex point and limbus center. The segmentation models exhibited high performance, with 96.88% dice similarity coefficient (DSC) for the sclera segmentation and 95.71% DSC for the limbus segmentation. The mathematical algorithm was tested on two cranial nerve palsy patients to evaluate its ability to measure and compare ocular deviation in different directions. These results were consistent with the symptoms of such disorders. This algorithm successfully measured the distance of ocular deviation in patients with strabismus. With complementation in the dimension calculations, we expect that this algorithm can be used further in clinical settings to diagnose and measure strabismus at a low cost. Copyright © 2022 Yena Christina Kang et al. | - |
dc.language | 영어 | - |
dc.language.iso | ENG | - |
dc.publisher | Hindawi Limited | - |
dc.title | Automated Mathematical Algorithm for Quantitative Measurement of Strabismus Based on Photographs of Nine Cardinal Gaze Positions | - |
dc.type | Article | - |
dc.identifier.wosid | 001013148500008 | - |
dc.identifier.doi | 10.1155/2022/9840494 | - |
dc.identifier.bibliographicCitation | BioMed research international, v.2022 | - |
dc.description.isOpenAccess | N | - |
dc.identifier.scopusid | 2-s2.0-85127504098 | - |
dc.citation.title | BioMed research international | - |
dc.citation.volume | 2022 | - |
dc.type.docType | Article | - |
dc.publisher.location | 영국 | - |
dc.relation.journalResearchArea | Biotechnology & Applied Microbiology | - |
dc.relation.journalResearchArea | Research & Experimental Medicine | - |
dc.relation.journalWebOfScienceCategory | Biotechnology & Applied Microbiology | - |
dc.relation.journalWebOfScienceCategory | Medicine, Research & Experimental | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.
1342, Seongnam-daero, Sujeong-gu, Seongnam-si, Gyeonggi-do, Republic of Korea(13120)031-750-5114
COPYRIGHT 2020 Gachon University All Rights Reserved.
Certain data included herein are derived from the © Web of Science of Clarivate Analytics. All rights reserved.
You may not copy or re-distribute this material in whole or in part without the prior written consent of Clarivate Analytics.