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Analysis of Macular Thickness Deviation Maps for Diagnosis of Glaucoma

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Advances in Visual Computing (ISVC 2021)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 13018))

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Abstract

There is a growing number of studies showing that analysis of macular parameters provides additional information about ganglion cell loss in glaucoma and compliments traditional markers of glaucoma. In this paper, we develop an image processing pipeline for the macular thickness deviation maps generated by Heidelberg Spectralis optical coherence tomography (OCT) to evaluate the information within the macular measurements for diagnosing glaucoma. Logistic regression is applied to analyze features extracted from the deviation maps and the strength of their relationship with the diagnosis of glaucoma. Our experimental results show that the proportion of regions with thickness significantly below the normative range in the nerve fiber layer thickness deviation maps can be used to detect glaucoma with an accuracy of up to 70.16%. Moreover, the ganglion cell layer deviation maps also possess significant diagnostic ability for detection of glaucoma, which can be combined with the traditional assessments of the optic nerve head and peripapillary retinal nerve fiber layer to improve the reliability of glaucoma diagnosis.

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Author information

Authors and Affiliations

  1. California State University Los Angeles, Los Angeles, CA, 90032, USA

    Bingnan Zhou, Jung S. Lim, Negin Forouzesh & Navid Amini

  2. University of California Los Angeles, Los Angeles, CA, 90095, USA

    Farnaz Mohammadi & Navid Amini

  3. Arizona State University, Tempe, AZ, 85281, USA

    Hassan Ghasemzadeh

Authors
  1. Bingnan Zhou
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  2. Farnaz Mohammadi
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  3. Jung S. Lim
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  4. Negin Forouzesh
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  5. Hassan Ghasemzadeh
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  6. Navid Amini
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Corresponding author

Correspondence to Navid Amini .

Editor information

Editors and Affiliations

  1. University of Nevada, Reno, NV, USA

    George Bebis

  2. University of Texas at Arlington, Arlington, TX, USA

    Vassilis Athitsos

  3. University of South Carolina, Columbia, SC, USA

    Tong Yan

  4. City University of Hong Kong, Kowloon, Hong Kong

    Manfred Lau

  5. School of Engineering and Computing, University of Durham, Durham, Durham, UK

    Frederick Li

  6. Airbnb, New York, NY, USA

    Conglei Shi

  7. Peking University, Beijing, China

    Xiaoru Yuan

  8. Purdue University, West Lafayette, IN, USA

    Christos Mousas

  9. IST, School of Modeling, Simulation, and Training, Orlando, FL, USA

    Gerd Bruder

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Zhou, B., Mohammadi, F., Lim, J.S., Forouzesh, N., Ghasemzadeh, H., Amini, N. (2021). Analysis of Macular Thickness Deviation Maps for Diagnosis of Glaucoma. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2021. Lecture Notes in Computer Science(), vol 13018. Springer, Cham. https://doi.org/10.1007/978-3-030-90436-4_5

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  • DOI: https://doi.org/10.1007/978-3-030-90436-4_5

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-90435-7

  • Online ISBN: 978-3-030-90436-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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