Accuracy of ultra-wide-field fundus ophthalmoscopy-assisted deep learning, a machine-learning technology, for detecting age-related macular degeneration

• Published in: International ophthalmology Vol. 39; no. 6; pp. 1269 - 1275
• Main Authors: Matsuba, Shinji, Tabuchi, Hitoshi, Ohsugi, Hideharu, Enno, Hiroki, Ishitobi, Naofumi, Masumoto, Hiroki, Kiuchi, Yoshiaki
• Format: Journal Article
• Language: English
• Published: Dordrecht Springer Netherlands 01.06.2019; Springer Nature B.V
• Subjects: Accuracy; Age; Age related diseases; Artificial neural networks; Deep learning; Diagnostic systems; Exudation; Learning algorithms; Machine learning; Macular degeneration; Medical imaging; Medical personnel; Medicine; Medicine & Public Health; Neural networks; Ophthalmology; Original Paper; Sensitivity; Telemedicine; Ultra-wide-field scanning laser ophthalmoscope; Pattern recognition; Telemedicine; Neural networks; Age-related macular degeneration
• DOI: 10.1007/s10792-018-0940-0
• ISSN: 0165-5701; 1573-2630

Purpose To predict exudative age-related macular degeneration (AMD), we combined a deep convolutional neural network (DCNN), a machine-learning algorithm, with Optos, an ultra-wide-field fundus imaging system. Methods First, to evaluate the diagnostic accuracy of DCNN, 364 photographic images (AMD: 137) were amplified and the area under the curve (AUC), sensitivity and specificity were examined. Furthermore, in order to compare the diagnostic abilities between DCNN and six ophthalmologists, we prepared yield 84 sheets comprising 50% of normal and wet-AMD data each, and calculated the correct answer rate, specificity, sensitivity, and response times. Results DCNN exhibited 100% sensitivity and 97.31% specificity for wet-AMD images, with an average AUC of 99.76%. Moreover, comparing the diagnostic abilities of DCNN versus six ophthalmologists, the average accuracy of the DCNN was 100%. On the other hand, the accuracy of ophthalmologists, determined only by Optos images without a fundus examination, was 81.9%. Conclusion A combination of DCNN with Optos images is not better than a medical examination; however, it can identify exudative AMD with a high level of accuracy. Our system is considered useful for screening and telemedicine.