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Computer-Aided Diagnosis of Anterior Segment Eye Abnormalities using Visible Wavelength Image Analysis Based Machine Learning

  • Image & Signal Processing
  • Published:
Journal of Medical Systems Aims and scope Submit manuscript

Abstract

Eye disease is a major health problem among the elderly people. Cataract and corneal arcus are the major abnormalities that exist in the anterior segment eye region of aged people. Hence, computer-aided diagnosis of anterior segment eye abnormalities will be helpful for mass screening and grading in ophthalmology. In this paper, we propose a multiclass computer-aided diagnosis (CAD) system using visible wavelength (VW) eye images to diagnose anterior segment eye abnormalities. In the proposed method, the input VW eye images are pre-processed for specular reflection removal and the iris circle region is segmented using a circular Hough Transform (CHT)-based approach. The first-order statistical features and wavelet-based features are extracted from the segmented iris circle and used for classification. The Support Vector Machine (SVM) by Sequential Minimal Optimization (SMO) algorithm was used for the classification. In experiments, we used 228 VW eye images that belong to three different classes of anterior segment eye abnormalities. The proposed method achieved a predictive accuracy of 96.96% with 97% sensitivity and 99% specificity. The experimental results show that the proposed method has significant potential for use in clinical applications.

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Acknowledgments

We would like to thank Dr. N. Ezhilvathani, Head, Department of Ophthalmology, Indira Gandhi Medical College and Research Institute (IGMC&RI), Puducherry for her valuable suggestions and support during the eye image data collection process of this research work.

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Authors and Affiliations

  1. Department of Electronics and Communication Engineering, Pondicherry Engineering College, Puducherry, India

    S.V. Mahesh Kumar & R. Gunasundari

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  1. S.V. Mahesh Kumar
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  2. R. Gunasundari
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Corresponding author

Correspondence to S.V. Mahesh Kumar.

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None declared.

Informed Consent

This study was approved by the Director of the medical review board, Indira Gandhi Medical College and Research Institute, Puducherry. Also, the informed written consent form was obtained from all individual volunteers participated in this study.

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This article is part of the Topical Collection on Image & Signal Processing

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S.V., M., R., G. Computer-Aided Diagnosis of Anterior Segment Eye Abnormalities using Visible Wavelength Image Analysis Based Machine Learning. J Med Syst 42, 128 (2018). https://doi.org/10.1007/s10916-018-0980-z

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  • DOI: https://doi.org/10.1007/s10916-018-0980-z

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