Deep Learning Techniques for Diabetic Retinopathy Detection.

Journal: Current medical imaging
Published Date:

Abstract

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.

Authors

  • Sehrish Qummar
    Department of Computer Science, COMSATS University Islamabad, Abbottabad Campus, Abbottabad, Pakistan.
  • Fiaz Gul Khan
    Department of Computer Science COMSATS Institute of IT, Abbottabad 22060, Pakistan. sajidshah@ciit.net.pk.
  • Sajid Shah
    College of Computer and Information Sciences, Prince Sultan University, Riyadh, Saudi Arabia.
  • Ahmad Khan
    Department of Computer Science, COMSATS University Islamabad, Abbottabad Campus, Abbottabad, Pakistan.
  • Ahmad Din
    Department of Computer Science, COMSATS University Islamabad, Abbottabad Campus, Abbottabad, Pakistan.
  • Jinfeng Gao
    College of Information Engineering, Huanghuai University, Henan 463000, China; Henan Key Laboratory of Smart Lighting, Henan 463000, China. Electronic address: hhgaostudy@163.tom.