Abira Bright B., Lakshmi Parvathi M., Vani Damodaran
{"title":"基于实时眼动追踪系统的手持式光学相干断层扫描系统运动估计","authors":"Abira Bright B., Lakshmi Parvathi M., Vani Damodaran","doi":"10.18287/jbpe23.09.030314","DOIUrl":null,"url":null,"abstract":"Optical coherence tomography (OCT) is the clinical golden standard for cross-sectional imaging of the eye. The majority of clinical ophthalmic OCT systems are table-top devices that need the patient to align with the chinrest in order to capture a motion-free image. Portable OCT devices are used to perform retinal imaging on infants or patients who are confined to beds. Eye movements and relative motion between the patient and the imaging probe make interpretation and registration challenging and become a barrier to high-resolution ocular imaging. Thus, an OCT scanner with an automated real-time eye tracking system and a movement mapping for correction mechanism is required to overcome such motions. The aim of this work is to develop an algorithm to track pupil motion and allow motion-corrected imaging of the retina without the requirement of chinrest, fixation of the target, or seating chair and to minimize the requirement of skillset to operate and to correct motion artifacts. Two algorithms based on landmark and threshold were developed, capable of identifying and monitoring eye movements. The acquired output value of both algorithms was compared with the manually calculated actual center value of the pupil. The average deviation from the actual location was found to be 0.2~0.6 for the landmark and 0.4~0.9 for the threshold-based algorithm. In this study, it is observed that iris localization and gaze direction estimation is more accurate in the landmark-based system compared to the threshold-based eye-tracking system.","PeriodicalId":52398,"journal":{"name":"Journal of Biomedical Photonics and Engineering","volume":"111 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Motion Estimation of Handheld Optical Coherence Tomography System using Real-Time Eye Tracking System\",\"authors\":\"Abira Bright B., Lakshmi Parvathi M., Vani Damodaran\",\"doi\":\"10.18287/jbpe23.09.030314\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Optical coherence tomography (OCT) is the clinical golden standard for cross-sectional imaging of the eye. The majority of clinical ophthalmic OCT systems are table-top devices that need the patient to align with the chinrest in order to capture a motion-free image. Portable OCT devices are used to perform retinal imaging on infants or patients who are confined to beds. Eye movements and relative motion between the patient and the imaging probe make interpretation and registration challenging and become a barrier to high-resolution ocular imaging. Thus, an OCT scanner with an automated real-time eye tracking system and a movement mapping for correction mechanism is required to overcome such motions. The aim of this work is to develop an algorithm to track pupil motion and allow motion-corrected imaging of the retina without the requirement of chinrest, fixation of the target, or seating chair and to minimize the requirement of skillset to operate and to correct motion artifacts. Two algorithms based on landmark and threshold were developed, capable of identifying and monitoring eye movements. The acquired output value of both algorithms was compared with the manually calculated actual center value of the pupil. The average deviation from the actual location was found to be 0.2~0.6 for the landmark and 0.4~0.9 for the threshold-based algorithm. In this study, it is observed that iris localization and gaze direction estimation is more accurate in the landmark-based system compared to the threshold-based eye-tracking system.\",\"PeriodicalId\":52398,\"journal\":{\"name\":\"Journal of Biomedical Photonics and Engineering\",\"volume\":\"111 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-09-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Biomedical Photonics and Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.18287/jbpe23.09.030314\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"Physics and Astronomy\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Biomedical Photonics and Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.18287/jbpe23.09.030314","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Physics and Astronomy","Score":null,"Total":0}
Motion Estimation of Handheld Optical Coherence Tomography System using Real-Time Eye Tracking System
Optical coherence tomography (OCT) is the clinical golden standard for cross-sectional imaging of the eye. The majority of clinical ophthalmic OCT systems are table-top devices that need the patient to align with the chinrest in order to capture a motion-free image. Portable OCT devices are used to perform retinal imaging on infants or patients who are confined to beds. Eye movements and relative motion between the patient and the imaging probe make interpretation and registration challenging and become a barrier to high-resolution ocular imaging. Thus, an OCT scanner with an automated real-time eye tracking system and a movement mapping for correction mechanism is required to overcome such motions. The aim of this work is to develop an algorithm to track pupil motion and allow motion-corrected imaging of the retina without the requirement of chinrest, fixation of the target, or seating chair and to minimize the requirement of skillset to operate and to correct motion artifacts. Two algorithms based on landmark and threshold were developed, capable of identifying and monitoring eye movements. The acquired output value of both algorithms was compared with the manually calculated actual center value of the pupil. The average deviation from the actual location was found to be 0.2~0.6 for the landmark and 0.4~0.9 for the threshold-based algorithm. In this study, it is observed that iris localization and gaze direction estimation is more accurate in the landmark-based system compared to the threshold-based eye-tracking system.