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Texture based on geostatistic for glaucoma diagnosis from fundus eye image

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Abstract

Glaucoma is an ocular disorder that can permanently damage patient vision. Initially, it reduces the visual field, and may cause blindness. Effective methods for early detection is crucial for avoiding significant damages of the patient vision. The use of CAD (Computer-Aided Detection) and CADx (Computer-Aided Diagnosis) systems has contributed to increase the chances of detection and precise diagnoses, assisting experts’ decision making on treatment regarding glaucoma. This paper proposes a method that analyzes the texture of the optical disk image region to diagnose glaucoma. Such analysis is done using the Local Binary Pattern (LBP) to represent the optic disk region, and geostatistical functions to describe texture patterns. The obtained texture features are used for classification based on Support Vector Machine. The proposed method presented as best results a sensitivity of 95%, accuracy of 91% and specificity of 88% in the diagnosis of glaucoma. The method has proved to be promising in assisting glaucoma diagnosis.

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Authors and Affiliations

  1. Universidade Federal do Maranhao, Av. dos Portugueses, 1966, Bacanga, São Luís, Maranhão, 65080-805, Brazil

    Jefferson Alves de Sousa, Anselmo Cardoso de Paiva, João Dallyson Sousa de Almeida, Aristofanes Corrêa Silva & Geraldo Braz Junior

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

    Marcelo Gattass

Authors
  1. Jefferson Alves de Sousa
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  2. Anselmo Cardoso de Paiva
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  3. João Dallyson Sousa de Almeida
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  4. Aristofanes Corrêa Silva
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  5. Geraldo Braz Junior
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  6. Marcelo Gattass
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Correspondence to Jefferson Alves de Sousa.

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de Sousa, J.A., de Paiva, A.C., Sousa de Almeida, J.D. et al. Texture based on geostatistic for glaucoma diagnosis from fundus eye image. Multimed Tools Appl 76, 19173–19190 (2017). https://doi.org/10.1007/s11042-017-4608-y

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  • DOI: https://doi.org/10.1007/s11042-017-4608-y

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