arXiv Analytics

Sign in

arXiv:2101.09864 [cs.CV]AbstractReferencesReviewsResources

Applications of Deep Learning in Fundus Images: A Review

Tao Li, Wang Bo, Chunyu Hu, Hong Kang, Hanruo Liu, Kai Wang, Huazhu Fu

Published 2021-01-25Version 1

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.

Journal: Medical Image Analysis 2021
Categories: cs.CV, cs.AI
Related articles: Most relevant | Search more
arXiv:1706.09077 [cs.CV] (Published 2017-06-28)
Super-Resolution via Deep Learning
arXiv:1703.07479 [cs.CV] (Published 2017-03-22)
Knowledge Transfer for Melanoma Screening with Deep Learning
arXiv:1602.05531 [cs.CV] (Published 2016-02-17)
On the Use of Deep Learning for Blind Image Quality Assessment