@inproceedings{f06eb642cfcd476681a2a74872e8f21e,
title = "An affordable and easy-to-use diagnostic method for keratoconus detection using a smartphone",
abstract = "Recently, smartphones are used for disease diagnosis and healthcare. In this paper, we propose a novel affordable diagnostic method of detecting keratoconus using a smartphone. Keratoconus is usually detected in clinics with ophthalmic devices, which are large, expensive and not portable, and need to be operated by trained technicians. However, our proposed smartphone-based eye disease detection method is small, affordable, portable, and it can be operated by patients in a convenient way. The results show that the proposed keratoconus detection method detects severe, advanced, and moderate keratoconus with accuracies of 93%, 86%, 67%, respectively. Due to its convenience with these accuracies, the proposed keratoconus detection method is expected to be applied in detecting keratoconus at an earlier stage in an affordable way.",
keywords = "Cornea, Corneal topography, Image processing, Keratoconus, Smartphone",
author = "Behnam Askarian and Fatemehsadat Tabei and Amin Askarian and Chong, {Jo Woon}",
note = "Publisher Copyright: {\textcopyright} 2018 SPIE.; null ; Conference date: 12-02-2018 Through 15-02-2018",
year = "2018",
doi = "10.1117/12.2293765",
language = "English",
series = "Progress in Biomedical Optics and Imaging - Proceedings of SPIE",
publisher = "SPIE",
editor = "Kensaku Mori and Nicholas Petrick",
booktitle = "Medical Imaging 2018",
}