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Titel:

Machine Learning Techniques for Ophthalmic Data Processing: A Review.

Dokumenttyp:
Journal Article; Research Support, Non-U.S. Gov't; Review
Autor(en):
Sarhan, Mhd Hasan; Nasseri, M Ali; Zapp, Daniel; Maier, Mathias; Lohmann, Chris P; Navab, Nassir; Eslami, Abouzar
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...     »
Zeitschriftentitel:
IEEE J Biomed Health Inform
Jahr:
2020
Band / Volume:
24
Heft / Issue:
12
Seitenangaben Beitrag:
3338-3350
Volltext / DOI:
doi:10.1109/JBHI.2020.3012134
PubMed:
http://view.ncbi.nlm.nih.gov/pubmed/32750971
Print-ISSN:
2168-2194
TUM Einrichtung:
Klinik und Poliklinik für Augenheilkunde
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