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author:

Lin, J. (Lin, J..) [1] | Yu, L. (Yu, L..) [2] | Weng, Q. (Weng, Q..) [3] | Zheng, X. (Zheng, X..) [4]

Indexed by:

Scopus

Abstract:

Retinal image quality assessment (RIQA) is one of the key components in screening for diabetic retinopathy (DR). As one of the most serious complications of diabetes, DR has become a leading cause of blindness in adults globally. DR screening is essential to achieve early diagnosis so that effective treatment could be provided timely. However, the collected images of medically unsatisfactory quality always lead to failure of diagnosis and waste of ophthalmologists’ precious time. Hence, the first step in a good DR screening program is verifying retinal images of good quality. In this paper, we provide a systematic review on automated assessment of retinal image quality for DR screening. Scheme and parameters for RIQA are firstly presented. Next, we provide detailed understanding of the existing RIQA techniques, algorithms and methodologies, including brief description and analysis of each existing state-of-art approaches and comparison between such methods. Datasets and evaluation metrics are also illustrated. Finally, several challenges and future research directions are summarized and discussed. © 2019, Springer Science+Business Media, LLC, part of Springer Nature.

Keyword:

Diabetic retinopathy; Retinal image; Retinal image quality assessment; Screening

Community:

  • [ 1 ] [Lin, J.]College of Physics and Information Engineering, Fuzhou University, Fujian, China
  • [ 2 ] [Lin, J.]College of Mathematics and Computer Science, Fuzhou University, Fujian, China
  • [ 3 ] [Lin, J.]Fujian Key Laboratory of Network Computing and Intelligent Information Processing (Fuzhou University), Fujian, China
  • [ 4 ] [Yu, L.]College of Physics and Information Engineering, Fuzhou University, Fujian, China
  • [ 5 ] [Weng, Q.]College of Mathematics and Computer Science, Fuzhou University, Fujian, China
  • [ 6 ] [Zheng, X.]College of Mathematics and Computer Science, Fuzhou University, Fujian, China
  • [ 7 ] [Zheng, X.]Fujian Key Laboratory of Network Computing and Intelligent Information Processing (Fuzhou University), Fujian, China

Reprint 's Address:

  • [Lin, J.]Fujian Key Laboratory of Network Computing and Intelligent Information Processing (Fuzhou University)China

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Source :

Multimedia Tools and Applications

ISSN: 1380-7501

Year: 2020

Issue: 23-24

Volume: 79

Page: 16173-16199

2 . 7 5 7

JCR@2020

3 . 0 0 0

JCR@2023

ESI HC Threshold:149

JCR Journal Grade:2

CAS Journal Grade:3

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 0

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