Open Access<p>Identifying Diabetic Macular Edema and Other Retinal Diseases by Optical Coherence Tomography Image and Multiscale Deep Learning</p>
Author(s) -
Quan Zhang,
Zhiang Liu,
Jiaxu Li,
Guohua Liu
Publication year - 2020
Publication title -
diabetes, metabolic syndrome and obesity
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.853
H-Index - 43
ISSN - 1178-7007
DOI - 10.2147/dmso.s288419
Subject(s) - optical coherence tomography , artificial intelligence , interpretability , computer science , deep learning , drusen , medical imaging , fundus (uterus) , reliability (semiconductor) , pattern recognition (psychology) , machine learning , medicine , retinal , radiology , ophthalmology , power (physics) , physics , quantum mechanics
Diabetic Macular Edema has been one of the research hotspots all over the world. But as the global population continues to grow, the number of OCT images requiring manual analysis is becoming increasingly unaffordable. Medical images are often fuzzy due to the inherent physical processes of acquiring them. It is difficult for traditional algorithms to use low-quality data. And traditional algorithms usually only provide diagnostic results, which makes the reliability and interpretability of the model face challenges. To solve problem above, we proposed a more intuitive and robust diagnosis model with self-enhancement ability and clinical triage patients' ability.