Deep Learning Techniques for Diabetic Retinopathy Detection

被引:3
|
作者
Qummar, Sehrish [1 ,2 ]
Khan, Fiaz Gul [1 ]
Shah, Sajid [1 ]
Khan, Ahmad [1 ]
Din, Ahmad [1 ]
Gao, Jinfeng [2 ]
机构
[1] COMSATS Univ Islamabad, Dept Comp Sci, Abbottabad Campus, Abbottabad, Pakistan
[2] Huanghuai Univ, Dept Informat Engn, Zhumadian, Henan, Peoples R China
关键词
Diabetic retinopathy; deep learning; convolutional Neural Network; diabetes; machine learning; lesions detection; AUTOMATED DETECTION; NEURAL-NETWORK; IMAGES; ALGORITHMS; DIAGNOSIS; LESIONS; AREA;
D O I
10.2174/1573405616666200213114026
中图分类号
R8 [特种医学]; R445 [影像诊断学];
学科分类号
1002 ; 100207 ; 1009 ;
摘要
Diabetes occurs due to the excess of glucose in the blood that may affect many organs of the body. Elevated blood sugar in the body causes many problems including Diabetic Retinopathy (DR). DR occurs due to the mutilation of the blood vessels in the retina. The manual detection of DR by ophthalmologists is complicated and time-consuming. Therefore, automatic detection is required, and recently different machine and deep learning techniques have been applied to detect and classify DR. In this paper, we conducted a study of the various techniques available in the literature for the identification/classification of DR, the strengths and weaknesses of available datasets for each method, and provides the future directions. Moreover, we also discussed the different steps of detection, that are: segmentation of blood vessels in a retina, detection of lesions, and other abnormalities of DR.
引用
收藏
页码:1201 / 1213
页数:13
相关论文
共 50 条
  • [21] Diabetic retinopathy detection by optimized deep learning model
    Venubabu Rachapudi
    K. Subba Rao
    T. Subha Mastan Rao
    P. Dileep
    T.L. Deepika Roy
    Multimedia Tools and Applications, 2023, 82 : 27949 - 27971
  • [22] A deep learning model framework for diabetic retinopathy detection
    Padmapriya M.
    Pasupathy S.
    Sumathi R.
    Punitha V.
    International Journal of Networking and Virtual Organisations, 2022, 27 (02): : 107 - 124
  • [23] A Deep Learning Ensemble Approach for Diabetic Retinopathy Detection
    Qummar, Sehrish
    Khan, Fiaz Gul
    Shah, Sajid
    Khan, Ahmad
    Shamshirband, Shahaboddin
    Rehman, Zia Ur
    Khan, Iftikhar Ahmed
    Jadoon, Waqas
    IEEE ACCESS, 2019, 7 : 150530 - 150539
  • [24] Diabetic Retinopathy Severity Prediction Using Deep Learning Techniques
    Paul, Victer
    Paul, Bivek Benoy
    Raju, R.
    INTERNATIONAL JOURNAL OF INTELLIGENT INFORMATION TECHNOLOGIES, 2023, 19 (01)
  • [25] A Comprehensive Review of Diabetic Retinopathy Detection and Grading Based on Deep Learning and Metaheuristic Optimization Techniques
    A. Mary Dayana
    W. R. Sam Emmanuel
    Archives of Computational Methods in Engineering, 2023, 30 : 4565 - 4599
  • [26] A Comprehensive Review of Diabetic Retinopathy Detection and Grading Based on Deep Learning and Metaheuristic Optimization Techniques
    Dayana, A. Mary
    Emmanuel, W. R. Sam
    ARCHIVES OF COMPUTATIONAL METHODS IN ENGINEERING, 2023, 30 (07) : 4565 - 4599
  • [27] A broad study of machine learning and deep learning techniques for diabetic retinopathy based on feature extraction, detection and classification
    Sangeetha K.
    Valarmathi K.
    Kalaichelvi T.
    Subburaj S.
    Measurement: Sensors, 2023, 30
  • [28] A Comprehensive Study of Machine Learning Techniques for Diabetic Retinopathy Detection
    Kumari, Rachna
    Kumar, Sanjeev
    Godara, Sunila
    INTERNATIONAL CONFERENCE ON INNOVATIVE COMPUTING AND COMMUNICATIONS, ICICC 2022, VOL 3, 2023, 492 : 161 - 183
  • [29] Using Deep Learning Architectures for Detection and Classification of Diabetic Retinopathy
    Mohanty, Cheena
    Mahapatra, Sakuntala
    Acharya, Biswaranjan
    Kokkoras, Fotis
    Gerogiannis, Vassilis C.
    Karamitsos, Ioannis
    Kanavos, Andreas
    SENSORS, 2023, 23 (12)
  • [30] Deep Learning for Diabetic Retinopathy Early Detection and Severity Grading
    Bouslimi, Dhia Elhak
    Bouslimi, Yahia
    Echi, Afef Kacem
    Ben Ayed, Leila
    2024 IEEE 7TH INTERNATIONAL CONFERENCE ON ADVANCED TECHNOLOGIES, SIGNAL AND IMAGE PROCESSING, ATSIP 2024, 2024, : 165 - 170