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Evaluation of Deep Learning Networks for Keratoconus Detection Using Corneal Topographic Images

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Computer Vision and Image Processing (CVIP 2020)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1377))

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Abstract

Keratoconus is an eye disease of ‘deformation of corneal curvature’ caused due to ‘non-inflammatory progressive thinning’ resulting into loss of elasticity in cornea and protrudes a cone shape formation that ultimately reduces visual acuity. For many years, researchers have worked towards accurate detection of keratoconus (KCN) as it is essential checkup before any refractive surgery demanding quick as well as precise clinical diagnosis and treatments of keratoconus prior to LASIK. In our study, we have firstly derived two variants of the original corneal topographies namely ‘images with edges’ and ‘images with edges-and-mask’, as data sets. The deep neural network techniques such as Artificial Neural Network (ANN), Convolutional Neural Network (CNN) and pertained VGG16 model are applied on original ‘corneal topographies’ as well as on the two of its variants and the results obtained are presented.

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Author information

Authors and Affiliations

  1. Department of Computer Science, Gujarat University, Navrangpura, Ahmedabad, 380009, Gujarat, India

    Savita R. Gandhi, Jigna Satani, Karan Bhuva & Parth Patadiya

Authors
  1. Savita R. Gandhi
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  2. Jigna Satani
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  3. Karan Bhuva
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  4. Parth Patadiya
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Editor information

Editors and Affiliations

  1. Indian Institute of Information Technology Allahabad, Prayagraj, India

    Satish Kumar Singh

  2. Indian Institute of Technology Roorkee, Roorkee, India

    Partha Roy

  3. Indian Institute of Technology Roorkee, Roorkee, India

    Balasubramanian Raman

  4. Indian Institute of Information Technology Allahabad, Prayagraj, India

    P. Nagabhushan

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Gandhi, S.R., Satani, J., Bhuva, K., Patadiya, P. (2021). Evaluation of Deep Learning Networks for Keratoconus Detection Using Corneal Topographic Images. In: Singh, S.K., Roy, P., Raman, B., Nagabhushan, P. (eds) Computer Vision and Image Processing. CVIP 2020. Communications in Computer and Information Science, vol 1377. Springer, Singapore. https://doi.org/10.1007/978-981-16-1092-9_31

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  • DOI: https://doi.org/10.1007/978-981-16-1092-9_31

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-16-1091-2

  • Online ISBN: 978-981-16-1092-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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