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Glaucoma diagnosis in fundus eye images using diversity indexes

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Abstract

Glaucoma is the second major cause of vision loss worldwide. It is usually caused by the increase in the intraocular pressure, which damages the optic nerve resulting in gradual vision loss. Glaucoma is an asymptomatic disease in the initial stages. Early detection and treatment may prevent the vision loss. The head of the optic nerve (optic disc) is examined by using fundus eye images. Computer systems have been used to provide support in glaucoma diagnosis. This work proposes a method for glaucoma diagnosis using fundus eye images. Diversity indexes, which are typically used in ecological studies, are used in this work as texture descriptors in the optic disc region. Then, a feature selection procedure is performed using genetic algorithm and support vector machines (SVM) are used to classify fundus eye images in glaucomatous or normal. The proposed method obtained promising results for glaucoma diagnosis, reaching an accuracy of 93.41%, sensitivity of 92.83% and specificity of 93.69%.

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Acknowledgments

The authors acknowledge the Coordination for the Improvement of Higher Education Personnel (CAPES), the National Council for Scientific and Technological Development (CNPq), the Foundation for the Protection of Research and Scientific, the Technological Development of the State of Maranhão (FAPEMA) for financial support.

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Authors and Affiliations

  1. Federal University of Maranhão, São Luís, Maranhão, Brazil

    José Denes Lima Araújo, Johnatan Carvalho Souza, Otilio Paulo Silva Neto, Jefferson Alves de Sousa, João Dallyson Sousa de Almeida, Anselmo Cardoso de Paiva, Aristófanes Corrêa Silva & Geraldo Braz Junior

  2. Pontifical Catholic University of Rio de Janeiro, Rio de Janeiro, Brazil

    Marcelo Gattass

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  1. José Denes Lima Araújo
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  2. Johnatan Carvalho Souza
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Correspondence to José Denes Lima Araújo.

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Araújo, J.D.L., Souza, J.C., Neto, O.P.S. et al. Glaucoma diagnosis in fundus eye images using diversity indexes. Multimed Tools Appl 78, 12987–13004 (2019). https://doi.org/10.1007/s11042-018-6429-z

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