Applications of deep learning in fundus images: A review

被引：214

作者：

Li, Tao ^{[1
]}

Bo, Wang ^{[1
]}

Hu, Chunyu ^{[1
]}

Kang, Hong ^{[1
]}

Liu, Hanruo ^{[2
]}

Wang, Kai ^{[1
]}

Fu, Huazhu ^{[3
]}

机构：

[1] Nankai Univ, Coll Comp Sci, Tianjin 300350, Peoples R China

[2] Capital Med Univ, Beijing Tongren Hosp, Beijing 100730, Peoples R China

[3] Incept Inst Artificial Intelligence IIAI, Abu Dhabi, U Arab Emirates

来源：

MEDICAL IMAGE ANALYSIS | 2021年 / 69卷

关键词：

Fundus images; Deep learning; Eye diseases; CONVOLUTIONAL NEURAL-NETWORK; DIABETIC MACULAR EDEMA; OPTIC-NERVE HEAD; RETINAL BLOOD-VESSELS; CUP SEGMENTATION; RETINOPATHY; GLAUCOMA; PREVALENCE; VALIDATION; DISEASE;

D O I：

10.1016/j.media.2021.101971

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

The use of fundus images for the early screening of eye diseases is of great clinical importance. Due to its powerful performance, deep learning is becoming more and more popular in related applications, such as lesion segmentation, biomarkers segmentation, disease diagnosis and image synthesis. Therefore, it is very necessary to summarize the recent developments in deep learning for fundus images with a review paper. In this review, we introduce 143 application papers with a carefully designed hierarchy. Moreover, 33 publicly available datasets are presented. Summaries and analyses are provided for each task. Finally, limitations common to all tasks are revealed and possible solutions are given. We will also release and regularly update the state-of-the-art results and newly-released datasets at https://github.com/nkicsl/Fundus_Review to adapt to the rapid development of this field. ? 2021 Elsevier B.V. All rights reserved.

引用

页数：32

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