Glaucoma Detection Through Optical Coherence Tomograph Images

DOI

10.2991/978-94-6463-136-4_71How to use a DOI?

Keywords

Glaucoma; ONH; RNFL; Optic Disc; OCT; Fundus Image

Abstract

The Glaucoma is an eye disease; it is irreversible cause of blindness in worldwide, so need for early detection of glaucoma. For detection of glaucoma, in this research study we used Optical Coherence tomograph images for early diagnosis. For this work we collected 625 OCT dataset with normal and glaucomatous suspects. Here we did three experiments, in our first experiment from collected OCT datasets, we measured Average RNFL thickness, in second experiment, we extracted glaucoma affected are from OCT images and in third experiment we extracted Ganglion cell layer and inner membrane layer for the glaucoma detection. We performed machine learning classifications and we got good results using support vector machine, we got 71% accuracy and with K-Nearest Neighbor, we got 71% accuracy.

Copyright

© 2023 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Gangadevi C. Bedke
AU  - Mukti E. Jadhav
AU  - Swapnil Dongaonkar
AU  - Avinash Kadam
AU  - Bali Thorat
PY  - 2023
DA  - 2023/05/01
TI  - Glaucoma Detection Through Optical Coherence Tomograph Images
BT  - Proceedings of the International Conference on Applications of Machine Intelligence and Data Analytics (ICAMIDA 2022)
PB  - Atlantis Press
SP  - 810
EP  - 819
SN  - 2352-538X
UR  - https://doi.org/10.2991/978-94-6463-136-4_71
DO  - 10.2991/978-94-6463-136-4_71
ID  - Bedke2023
ER  -