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Conference on Innovations in Biomedical Engineering

IBE 2017: Innovations in Biomedical Engineering pp 43–51Cite as

Detection of Wet Age-related Macular Degeneration in OCT Images: A Case Study

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 623 ))

Abstract

Progress in medical imaging and computer vision has enabled us to rely on machines for the detection or diagnosis of many diseases, including eye-related problems. One of them is wet age-related macular degeneration (wet AMD) which is a type of age-related macular degeneration. Wet AMD causes the detachment of retinal pigment epithelium layer (RPE) – a condition referred to as pigment epithelium detachment (PED) – and also creates fluid fill region called choroidal neovascularization (CNV). In this paper we present a case study of detecting wet ADM in OCT images. We used a set of 51 images – 21 of sick eyes and 30 of healthy eyes. We employed feature extraction techniques to identify abnormalities in RPE layer (PED and CNV) along with the structural and textural properties of the RPE layer (gray level co-occurrence matrix, GLCM). Specifically, we considered four possible set of features and for each set we constructed k-NN, naive Bayes, support vector machine (SVM) and rule-based classifiers. The best classification performance was obtained for the features capturing the structural and textural properties of the RPE layer and for naive Bayes classifier (accuracy = 96.1%, sensitivity = 91.3%, specificity = 100.0%) and SVM classifier (accuracy = 94.1%, sensitivity = 100.0%, specificity = 93.7%). Our results confirm the usefulness of the features characterizing the RPE layer in the diagnosis of wet AMD.

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Author information

Authors and Affiliations

  1. Poznan University of Technology, Poznan, Poland

    Anam Haq & Szymon Wilk

Authors
  1. Anam Haq
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  2. Szymon Wilk
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Corresponding author

Correspondence to Anam Haq .

Editor information

Editors and Affiliations

  1. Department of Biomechatronics, Silesian University of Technology, Faculty of Biomedical Engineering, Zabrze, Poland

    Marek Gzik

  2. Department of Biosensors and Biomedical Signals Processing, Silesian University of Technology, Faculty of Biomedical Engineering, Zabrze, Poland

    Ewaryst Tkacz

  3. Department of Biomaterials and Medical Devices Engineering, Silesian University of Technology, Faculty of Biomedical Engineering, Zabrze, Poland

    Zbigniew Paszenda

  4. Dept. of Informatics and Medical Equipment, Silesian University of Technology, Faculty of Biomedical Engineering, Zabrze, Poland

    Ewa Piętka

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Haq, A., Wilk, S. (2018). Detection of Wet Age-related Macular Degeneration in OCT Images: A Case Study. In: Gzik, M., Tkacz, E., Paszenda, Z., Piętka, E. (eds) Innovations in Biomedical Engineering . IBE 2017. Advances in Intelligent Systems and Computing, vol 623 . Springer, Cham. https://doi.org/10.1007/978-3-319-70063-2_5

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  • DOI: https://doi.org/10.1007/978-3-319-70063-2_5

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-70062-5

  • Online ISBN: 978-3-319-70063-2

  • eBook Packages: EngineeringEngineering (R0)

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