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Automatic glaucoma screening using optic nerve head measurements and random forest classifier on fundus images

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Abstract

Glaucoma is an optic neuropathy that gradually steals the patient's sight by damaging the optic nerve head (which is responsible for transferring images from the eye to the brain). Causing an estimated 12.3% of global blindness, glaucoma is considered as the first leading cause of irreversible blindness in the world. This paper presents a novel eye fundus image analysis algorithm for the automatic measurement of fundus related glaucoma indicators; Cup to Disc Ratio (CDR), verification of the ISNT rule, Disc Damage Likelihood Scale (DDLS), and the classification of the input fundus into glaucoma or non-glaucoma case using a random forest model. The proposed method is applied on the public image database 'HRF', and a local database containing both, normal and glaucoma cases, and resulted sensitivity, specificity, and accuracy of 1, 0.93 and 0.97 respectively. This technique presented the highest classification accuracy compared to previous works studied in the state of the art; hence, it can be used as a computer aided glaucoma diagnosis system by ophthalmologists to assist in their screening routine.

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Data Availability

The authors declare that all data and materials used in this research support their published claims and comply with field standards.

Code availability

The data that support the findings of this study are available from the corresponding author (Mohamed Bouacheria), upon reasonable request.

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Acknowledgements

The authors would like to thank Dr. Z. Merrad for supervising and following up this work. Her expertise and knowledge in the field of ophthalmology and glaucoma have allowed a good orientation of this work, in addition, Frantz Fanon hospital for providing the data support needed in the course of the study.

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The authors received no specific funding for this work.

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Authors and Affiliations

  1. Department of Electrical Engineering, University of Blida 1, BP 270 road soumaa, Blida, Algeria

    Mohamed Bouacheria, Yazid Cherfa, Assia Cherfa & Noureddine Belkhamsa

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  1. Mohamed Bouacheria
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  2. Yazid Cherfa
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  3. Assia Cherfa
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  4. Noureddine Belkhamsa
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Contributions

MB and YC did data collection. MB implemented the model and analyzed data. MB wrote the manuscript with critical input from YC, AC and NB. All authors read and approved the final manuscript.

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Correspondence to Mohamed Bouacheria.

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Bouacheria, M., Cherfa, Y., Cherfa, A. et al. Automatic glaucoma screening using optic nerve head measurements and random forest classifier on fundus images. Phys Eng Sci Med 43, 1265–1277 (2020). https://doi.org/10.1007/s13246-020-00930-y

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  • DOI: https://doi.org/10.1007/s13246-020-00930-y

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