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Document type:
Journal Article; Research Support, Non-U.S. Gov't; Review 
Author(s):
Sarhan, Mhd Hasan; Nasseri, M Ali; Zapp, Daniel; Maier, Mathias; Lohmann, Chris P; Navab, Nassir; Eslami, Abouzar 
Title:
Machine Learning Techniques for Ophthalmic Data Processing: A Review. 
Abstract:
Machine learning and especially deep learning techniques are dominating medical image and data analysis. This article reviews machine learning approaches proposed for diagnosing ophthalmic diseases during the last four years. Three diseases are addressed in this survey, namely diabetic retinopathy, age-related macular degeneration, and glaucoma. The review covers over 60 publications and 25 public datasets and challenges related to the detection, grading, and lesion segmentation of the three con...    »
 
Journal title abbreviation:
IEEE J Biomed Health Inform 
Year:
2020 
Journal volume:
24 
Journal issue:
12 
Pages contribution:
3338-3350 
Print-ISSN:
2168-2194 
TUM Institution:
Klinik und Poliklinik für Augenheilkunde