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An affordable and easy-to-use diagnostic method for keratoconus detection using a smartphone
Author(s): Behnam Askarian; Fatemehsadat Tabei; Amin Askarian; Jo Woon Chong
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Paper 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.

Paper Details

Date Published: 27 February 2018
PDF: 6 pages
Proc. SPIE 10575, Medical Imaging 2018: Computer-Aided Diagnosis, 1057512 (27 February 2018); doi: 10.1117/12.2293765
Show Author Affiliations
Behnam Askarian, Texas Tech Univ. (United States)
Fatemehsadat Tabei, Texas Tech Univ. (United States)
Amin Askarian, Shiraz Univ. of Medical Sciences (Iran, Islamic Republic of)
Jo Woon Chong, Texas Tech Univ. (United States)

Published in SPIE Proceedings Vol. 10575:
Medical Imaging 2018: Computer-Aided Diagnosis
Nicholas Petrick; Kensaku Mori, Editor(s)

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