Literature DB >> 30448367

Diabetic retinopathy techniques in retinal images: A review.

Nadeem Salamat1, Malik M Saad Missen2, Aqsa Rashid3.   

Abstract

The diabetic retinopathy is the main reason of vision loss in people. Medical experts recognize some clinical, geometrical and haemodynamic features of diabetic retinopathy. These features include the blood vessel area, exudates, microaneurysm, hemorrhages and neovascularization, etc. In Computer Aided Diagnosis (CAD) systems, these features are detected in fundus images using computer vision techniques. In this paper, we review the methods of low, middle and high level vision for automatic detection and classification of diabetic retinopathy.We give a detailed review of 79 algorithms for detecting different features of diabetic retinopathy during the last eight years.
Copyright © 2018 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Blood vessels; Computer aided diagnosis; Diabetic retinopathy screening; Exudates; Optic disc

Mesh:

Year:  2018        PMID: 30448367     DOI: 10.1016/j.artmed.2018.10.009

Source DB:  PubMed          Journal:  Artif Intell Med        ISSN: 0933-3657            Impact factor:   5.326


  3 in total

1.  Microaneurysms segmentation with a U-Net based on recurrent residual convolutional neural network.

Authors:  Caixia Kou; Wei Li; Wei Liang; Zekuan Yu; Jianchen Hao
Journal:  J Med Imaging (Bellingham)       Date:  2019-06-19

Review 2.  Colorimetric and Electrochemical Screening for Early Detection of Diabetes Mellitus and Diabetic Retinopathy-Application of Sensor Arrays and Machine Learning.

Authors:  Georgina Faura; Gerard Boix-Lemonche; Anne Kristin Holmeide; Rasa Verkauskiene; Vallo Volke; Jelizaveta Sokolovska; Goran Petrovski
Journal:  Sensors (Basel)       Date:  2022-01-18       Impact factor: 3.576

3.  Microaneurysms detection in color fundus images using machine learning based on directional local contrast.

Authors:  Shengchun Long; Jiali Chen; Ante Hu; Haipeng Liu; Zhiqing Chen; Dingchang Zheng
Journal:  Biomed Eng Online       Date:  2020-04-15       Impact factor: 2.819

  3 in total

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