Optic Disc Preprocessing for Reliable Glaucoma Detection in Small Datasets

José E. Valdez-Rodríguez, Edgardo M. Felipe-Riverón and Hiram Calvo
Additional contact information
José E. Valdez-Rodríguez: Centro de Investigación en Computación, Instituto Politécnico Nacional, Mexico City 07738, Mexico
Edgardo M. Felipe-Riverón: Centro de Investigación en Computación, Instituto Politécnico Nacional, Mexico City 07738, Mexico
Hiram Calvo: Centro de Investigación en Computación, Instituto Politécnico Nacional, Mexico City 07738, Mexico

Mathematics, 2021, vol. 9, issue 18, 1-14

Abstract: Glaucoma detection is an important task, as this disease can affect the optic nerve, and this could lead to blindness. This can be prevented with early diagnosis, periodic controls, and treatment so that it can be stopped and prevent visual loss. Usually, the detection of glaucoma is carried out through various examinations such as tonometry, gonioscopy, pachymetry, etc. In this work, we carry out this detection by using images obtained through retinal cameras, in which we can observe the state of the optic nerve. This work addresses an accurate diagnostic methodology based on Convolutional Neural Networks (CNNs) to classify these optical images. Most works require a large number of images to train their CNN architectures, and most of them use the whole image to perform the classification. We will use a small dataset containing 366 examples to train the proposed CNN architecture and we will only focus on the analysis of the optic disc by extracting it from the full image, as this is the element that provides the most information about glaucoma. We experiment with different RGB channels and their combinations from the optic disc, and additionally, we extract depth information. We obtain accuracy values of 0.945, by using the GB and the full RGB combination, and 0.934 for the grayscale transformation. Depth information did not help, as it limited the best accuracy value to 0.934.

Keywords: glaucoma; convolutional neural networks; medical-diagnosis method; optic disc (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2021
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2227-7390/9/18/2237/pdf (application/pdf)
https://www.mdpi.com/2227-7390/9/18/2237/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jmathe:v:9:y:2021:i:18:p:2237-:d:633724

Access Statistics for this article

Mathematics is currently edited by Ms. Emma He

More articles in Mathematics from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().