Open AccessDETECTION OF MORPHOLOGIC PATTERNS OF DIABETIC MACULAR EDEMA USING A DEEP LEARNING APPROACH BASED ON OPTICAL COHERENCE TOMOGRAPHY IMAGES
Author(s) -
Qiaowei Wu,
Bin Zhang,
Yijun Hu,
Baoyi Liu,
Dan Cao,
Dawei Yang,
Qingsheng Peng,
Pingting Zhong,
Xiaomin Zeng,
Yu Xiao,
Cong Liu,
Ying Fang,
Songfu Feng,
Manqing Huang,
Hongmin Cai,
Xiaohong Yang,
Honghua Yu
Publication year - 2021
Publication title -
retina
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.24
H-Index - 120
eISSN - 1539-2864
pISSN - 0275-004X
DOI - 10.1097/iae.0000000000002992
Subject(s) - optical coherence tomography , retinal , receiver operating characteristic , ophthalmology , macular edema , medicine , diabetic retinopathy , diabetic macular edema , serous fluid , occlusion , pathology , surgery , diabetes mellitus , endocrinology
To develop a deep learning (DL) model to detect morphologic patterns of diabetic macular edema (DME) based on optical coherence tomography (OCT) images.