Cargando…
KeratoDetect: Keratoconus Detection Algorithm Using Convolutional Neural Networks
Keratoconus (KTC) is a noninflammatory disorder characterized by progressive thinning, corneal deformation, and scarring of the cornea. The pathological mechanisms of this condition have been investigated for a long time. In recent years, this disease has come to the attention of many research cente...
Autores principales: | , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2019
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6364125/ https://www.ncbi.nlm.nih.gov/pubmed/30809255 http://dx.doi.org/10.1155/2019/8162567 |
_version_ | 1783393206563504128 |
---|---|
author | Lavric, Alexandru Valentin, Popa |
author_facet | Lavric, Alexandru Valentin, Popa |
author_sort | Lavric, Alexandru |
collection | PubMed |
description | Keratoconus (KTC) is a noninflammatory disorder characterized by progressive thinning, corneal deformation, and scarring of the cornea. The pathological mechanisms of this condition have been investigated for a long time. In recent years, this disease has come to the attention of many research centers because the number of people diagnosed with keratoconus is on the rise. In this context, solutions that facilitate both the diagnostic and treatment options are quickly needed. The main contribution of this paper is the implementation of an algorithm that is able to determine whether an eye is affected or not by keratoconus. The KeratoDetect algorithm analyzes the corneal topography of the eye using a convolutional neural network (CNN) that is able to extract and learn the features of a keratoconus eye. The results show that the KeratoDetect algorithm ensures a high level of performance, obtaining an accuracy of 99.33% on the data test set. KeratoDetect can assist the ophthalmologist in rapid screening of its patients, thus reducing diagnostic errors and facilitating treatment. |
format | Online Article Text |
id | pubmed-6364125 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Hindawi |
record_format | MEDLINE/PubMed |
spelling | pubmed-63641252019-02-26 KeratoDetect: Keratoconus Detection Algorithm Using Convolutional Neural Networks Lavric, Alexandru Valentin, Popa Comput Intell Neurosci Research Article Keratoconus (KTC) is a noninflammatory disorder characterized by progressive thinning, corneal deformation, and scarring of the cornea. The pathological mechanisms of this condition have been investigated for a long time. In recent years, this disease has come to the attention of many research centers because the number of people diagnosed with keratoconus is on the rise. In this context, solutions that facilitate both the diagnostic and treatment options are quickly needed. The main contribution of this paper is the implementation of an algorithm that is able to determine whether an eye is affected or not by keratoconus. The KeratoDetect algorithm analyzes the corneal topography of the eye using a convolutional neural network (CNN) that is able to extract and learn the features of a keratoconus eye. The results show that the KeratoDetect algorithm ensures a high level of performance, obtaining an accuracy of 99.33% on the data test set. KeratoDetect can assist the ophthalmologist in rapid screening of its patients, thus reducing diagnostic errors and facilitating treatment. Hindawi 2019-01-23 /pmc/articles/PMC6364125/ /pubmed/30809255 http://dx.doi.org/10.1155/2019/8162567 Text en Copyright © 2019 Alexandru Lavric and Popa Valentin. http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Lavric, Alexandru Valentin, Popa KeratoDetect: Keratoconus Detection Algorithm Using Convolutional Neural Networks |
title | KeratoDetect: Keratoconus Detection Algorithm Using Convolutional Neural Networks |
title_full | KeratoDetect: Keratoconus Detection Algorithm Using Convolutional Neural Networks |
title_fullStr | KeratoDetect: Keratoconus Detection Algorithm Using Convolutional Neural Networks |
title_full_unstemmed | KeratoDetect: Keratoconus Detection Algorithm Using Convolutional Neural Networks |
title_short | KeratoDetect: Keratoconus Detection Algorithm Using Convolutional Neural Networks |
title_sort | keratodetect: keratoconus detection algorithm using convolutional neural networks |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6364125/ https://www.ncbi.nlm.nih.gov/pubmed/30809255 http://dx.doi.org/10.1155/2019/8162567 |
work_keys_str_mv | AT lavricalexandru keratodetectkeratoconusdetectionalgorithmusingconvolutionalneuralnetworks AT valentinpopa keratodetectkeratoconusdetectionalgorithmusingconvolutionalneuralnetworks |