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Automated Framework for Screening of Glaucoma Through Cloud Computing

  • M. Soorya
  • Ashish Issac
  • Malay Kishore DuttaEmail author
Image & Signal Processing
Part of the following topical collections:
  1. Image & Signal Processing

Abstract

In recent times, the use of computer aided diagnosis for detection of Glaucoma from fundus images has been prevalent. In the proposed work, a cloud based system is proposed for automatic and real-time screening of Glaucoma with the use of automatic image processing techniques. The proposed system offers scalability to the developers and easy accessibility to the consumers. The proposed system is device and location independent. The input digital image is analyzed and a comprehensive diagnostic report is generated consisting of detailed analysis of indicative medical parameters like optic-cup-to-disc ratio, optic neuro-retinal rim, ISNT rules making the report informative and clinically significant. With recent advances in the field of communication technologies, the internet facilities are available that make the proposed system an efficient and economical method for initial screening and offer preventive and diagnostic steps in early disease intervention and management. The proposed system can perform an initial screening test in an average time of 6 s on high resolution fundus images. The proposed system has been tested on a fundus database and an average sensitivity of 93.7% has been achieved for Glaucoma cases. In places where there is scarcity of trained ophthalmologists and lack of awareness of such diseases, the cloud based system can be used as an effective diagnostic assistive tool.

Keywords

Glaucoma Optic disc Retinal vessels ISNT rule Fundus images Cloud computing Web application Docker Heroku Django Base64 encoding OpenCV 

Notes

Acknowledgements

This work was supported in part by the Grants from Department of Science and Technology, No. DST/TSG/ICT/2013/37. Also, the authors express their thankfulness to Dr. S.C. Gupta, Medical Director of Venu Eye Research Centre for his contribution in classification of the images.

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Department of Computer Science and EngineeringAmity UniversityNoidaIndia
  2. 2.Department of Electronics and Communication EngineeringAmity UniversityNoidaIndia
  3. 3.Center for Advanced StudiesDr. A.P.J. Abdul Kalam Technical UniversityLucknowIndia

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