Automated Detection of Eye Related Diseases Using Digital Image Processing

  • Shailesh Kumar
  • Shashwat Pathak
  • Basant KumarEmail author


This chapter presents techniques for automated detection of various eye diseases using digital image processing. Human eyes suffer from variety of abnormalities due to aging, trauma and disease like diabetes. The leading causes of blindness throughout the world are cataract, glaucoma, macular degeneration, diabetic retinopathy, retinal detachment and diabetic macular edema. These eye diseases are detected and diagnosed by ophthalmologist and trained technicians. The imaging systems needed for detection of abnormalities are ophthalmoscopy, fundus photography, optical coherence tomography, ultrasound imaging, and Heidelberg retinal tomography. In developing countries like India, lack of eye care centres and non-availability of ophthalmologists are very common in rural and remote areas. Early detection, followed by appropriate medical treatment of various eye diseases can solve this problem to a large extent. Automated detection of eye diseases through analysis of different types of medical images provides a better alternative for timely diagnosis and treatment of the eye diseases. In general, the steps involved in image processing based automated diagnostic techniques are image acquisition, pre-processing, extraction of region of interest, feature extraction, and classification. The need for automated diagnosis system, study of various imaging techniques, current status and brief explanation of various eye diseases detection algorithms have been discussed in this chapter.


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© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Department of ECE, Motilal Nehru NIT AllahabadPrayagrajIndia

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