Detection of Glaucoma Using OCT Images

Asmitha Krishnakumar; Ahmad Ryad Soobhany

doi:10.1007/978-981-96-1758-6_25

Detection of Glaucoma Using OCT Images

Asmitha Krishnakumar, Ahmad Ryad Soobhany

School of Mathematical & Computer Sciences

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

Glaucoma is a chronic eye condition that results in damage to the optic nerve, which leads to permanent blindness if it is not diagnosed and treated early. As of now, there are no treatments for curing glaucoma; thus, early detection might halt its progression. There are several imaging techniques used in detection of glaucoma, and optical coherence tomography (OCT) has gained prominence due to its ability to provide high-resolution images. However, manual observation and diagnosis by ophthalmologists are labor-intensive. This study proposes a novel method for automated detection of glaucoma by using YOLOv5s, which is an object detection model, applied to OCT images of patients both with and without glaucoma. The preliminary results are encouraging and achieved a detection accuracy of 99.3%.

Original language	English
Title of host publication	Proceedings of International Conference on Information Technology and Applications
Subtitle of host publication	ICITA 2024
Editors	Abrar Ullah, Sajid Anwar
Publisher	Springer
Pages	295-307
Number of pages	13
Volume	1248
ISBN (Electronic)	9789819617586
ISBN (Print)	9789819617579
DOIs	https://doi.org/10.1007/978-981-96-1758-6_25
Publication status	Published - 15 Jun 2025
Event	18th International Conference on Information Technology and Applications 2024 - Sydney, Australia Duration: 17 Oct 2024 → 19 Oct 2024 https://2024.icita.world/#/

Publication series

Name	Lecture Notes in Networks and Systems
Volume	1248
ISSN (Print)	2367-3370
ISSN (Electronic)	2367-3389

Conference

Conference	18th International Conference on Information Technology and Applications 2024
Abbreviated title	ICITA 2024
Country/Territory	Australia
City	Sydney
Period	17/10/24 → 19/10/24
Internet address	https://2024.icita.world/#/

Keywords

Glaucoma detection
Object detection
Optical coherence tomography
YOLOv5s

ASJC Scopus subject areas

Control and Systems Engineering
Signal Processing
Computer Networks and Communications

Access to Document

10.1007/978-981-96-1758-6_25

Cite this

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title = "Detection of Glaucoma Using OCT Images",

abstract = "Glaucoma is a chronic eye condition that results in damage to the optic nerve, which leads to permanent blindness if it is not diagnosed and treated early. As of now, there are no treatments for curing glaucoma; thus, early detection might halt its progression. There are several imaging techniques used in detection of glaucoma, and optical coherence tomography (OCT) has gained prominence due to its ability to provide high-resolution images. However, manual observation and diagnosis by ophthalmologists are labor-intensive. This study proposes a novel method for automated detection of glaucoma by using YOLOv5s, which is an object detection model, applied to OCT images of patients both with and without glaucoma. The preliminary results are encouraging and achieved a detection accuracy of 99.3%.",

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booktitle = "Proceedings of International Conference on Information Technology and Applications",

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Krishnakumar, A & Soobhany, AR 2025, Detection of Glaucoma Using OCT Images. in A Ullah & S Anwar (eds), Proceedings of International Conference on Information Technology and Applications: ICITA 2024. vol. 1248, Lecture Notes in Networks and Systems, vol. 1248, Springer, pp. 295-307, 18th International Conference on Information Technology and Applications 2024, Sydney, Australia, 17/10/24. https://doi.org/10.1007/978-981-96-1758-6_25

Detection of Glaucoma Using OCT Images. / Krishnakumar, Asmitha; Soobhany, Ahmad Ryad.
Proceedings of International Conference on Information Technology and Applications: ICITA 2024. ed. / Abrar Ullah; Sajid Anwar. Vol. 1248 Springer, 2025. p. 295-307 (Lecture Notes in Networks and Systems; Vol. 1248).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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AU - Soobhany, Ahmad Ryad

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PY - 2025/6/15

Y1 - 2025/6/15

N2 - Glaucoma is a chronic eye condition that results in damage to the optic nerve, which leads to permanent blindness if it is not diagnosed and treated early. As of now, there are no treatments for curing glaucoma; thus, early detection might halt its progression. There are several imaging techniques used in detection of glaucoma, and optical coherence tomography (OCT) has gained prominence due to its ability to provide high-resolution images. However, manual observation and diagnosis by ophthalmologists are labor-intensive. This study proposes a novel method for automated detection of glaucoma by using YOLOv5s, which is an object detection model, applied to OCT images of patients both with and without glaucoma. The preliminary results are encouraging and achieved a detection accuracy of 99.3%.

AB - Glaucoma is a chronic eye condition that results in damage to the optic nerve, which leads to permanent blindness if it is not diagnosed and treated early. As of now, there are no treatments for curing glaucoma; thus, early detection might halt its progression. There are several imaging techniques used in detection of glaucoma, and optical coherence tomography (OCT) has gained prominence due to its ability to provide high-resolution images. However, manual observation and diagnosis by ophthalmologists are labor-intensive. This study proposes a novel method for automated detection of glaucoma by using YOLOv5s, which is an object detection model, applied to OCT images of patients both with and without glaucoma. The preliminary results are encouraging and achieved a detection accuracy of 99.3%.

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Detection of Glaucoma Using OCT Images

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Keywords

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