Glaucoma Detection Using Machine Learning
International Journal of Science and Research (IJSR)

International Journal of Science and Research (IJSR)
www.ijsr.net | Open Access | Fully Refereed | Peer Reviewed International Journal

ISSN: 2319-7064

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Research Paper | Computer Science & Engineering | India | Volume 10 Issue 4, April 2021

Glaucoma Detection Using Machine Learning

Sharanya S

Glaucoma is an eye disease if not detected in the early stage leads to permanent blindness. It is the second leading cause for eye blindness. The fundus camera is a type of modern imaging device that is used to examine the internal structure of the eye. Some of the methods used to detect glaucoma include the Topcon image net method, optical coherence tomography, and the retinal nerve fibre layer analyser. However due to high cost and lack of research in this field optic cup to- disc ratio is used to detect the glaucoma. To determine the glaucomatous damage, the appearance of the optic cup plays an important role. The cup enlarges with the advancement of glaucoma occupying most of the disc area. The optic cup-to disc ratio compares the diameter of the optic cup portion of the optic disc with the total diameter of the optic disc. The manual examination of optic disk and optic cup is time consuming. Hence automatic glaucoma detecting algorithm is developed. However, enlargement of optic cup itself is not indication of glaucoma because optic cupping may occur without glaucoma due to hereditary factor.

Keywords: Machine learning, Glaucoma, kernel, MATLAB, CNN, Rim-One, ConvNets

Edition: Volume 10 Issue 4, April 2021

Pages: 28 - 37

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How to Cite this Article?

Sharanya S, "Glaucoma Detection Using Machine Learning", International Journal of Science and Research (IJSR), https://www.ijsr.net/search_index_results_paperid.php?id=SR21328181208, Volume 10 Issue 4, April 2021, 28 - 37

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