Survey Analysis of Automatic Detection and Grading of Cataract Using Different Imaging Modalities

  • Isma Shaheen
  • Anam Tariq
Part of the EAI/Springer Innovations in Communication and Computing book series (EAISICC)


Cataract is the most common ocular disease mainly developed during old age. It occurs due to the buildup of protein at lens over a long period of time which makes the lens cloudy. Early and accurate diagnosis of cataract helps prevent vision loss. To alleviate the burden of ophthalmologist, many researchers working in the field of biomedical imaging developed a number of techniques for the automatic detection and grading of cataract. Imaging modalities used for this purpose includes slit-lamp images, retro-illumination images, digital/optical eye images, retinal images, and ultrasonic Nakagami images. In this paper, we review cataract detection and grading methodologies using these imaging modalities. For each imaging type, we analyze the possible methods and techniques applied so far. We also investigated the advantages and shortcomings of these techniques and methods and suggested the ways to improve the existing methods.


Nuclear cataract Cortical cataract Posterior subcapsular cataract [2] Slit-lamp images Retro-illumination images Retinal images Optical images and Nakagami images 


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© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Isma Shaheen
    • 1
  • Anam Tariq
    • 1
  1. 1.College of Electrical & Mechanical Engineering (CEME), National University of Science and TechnologyIslamabadPakistan

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