Analysis of Macular Thickness Deviation Maps for Diagnosis of Glaucoma

Bingnan Zhou; Farnaz Mohammadi; Jung S. Lim; Negin Forouzesh; Hassan Ghasemzadeh; Navid Amini

doi:10.1007/978-3-030-90436-4_5

Analysis of Macular Thickness Deviation Maps for Diagnosis of Glaucoma

Bingnan Zhou, Farnaz Mohammadi, Jung S. Lim, Negin Forouzesh, Hassan Ghasemzadeh, Navid Amini

Health Solutions, College of (CHS)

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

2 Scopus citations

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.

Original language	English (US)
Title of host publication	Advances in Visual Computing - 16th International Symposium, ISVC 2021, Proceedings
Editors	George Bebis, Vassilis Athitsos, Tong Yan, Manfred Lau, Frederick Li, Conglei Shi, Xiaoru Yuan, Christos Mousas, Gerd Bruder
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	53-64
Number of pages	12
ISBN (Print)	9783030904357
DOIs	https://doi.org/10.1007/978-3-030-90436-4_5
State	Published - 2021
Event	16th International Symposium on Visual Computing, ISVC 2021 - Virtual Online Duration: Oct 4 2021 → Oct 6 2021

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	13018 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	16th International Symposium on Visual Computing, ISVC 2021
City	Virtual Online
Period	10/4/21 → 10/6/21

Keywords

Feature selection
Glaucoma
Logistic regression
Machine learning
Macula

ASJC Scopus subject areas

Theoretical Computer Science
General Computer Science

Access to Document

10.1007/978-3-030-90436-4_5

Cite this

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 G. Bebis, V. Athitsos, T. Yan, M. Lau, F. Li, C. Shi, X. Yuan, C. Mousas, & G. Bruder (Eds.), Advances in Visual Computing - 16th International Symposium, ISVC 2021, Proceedings (pp. 53-64). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 13018 LNCS). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-030-90436-4_5

Analysis of Macular Thickness Deviation Maps for Diagnosis of Glaucoma. / Zhou, Bingnan; Mohammadi, Farnaz; Lim, Jung S. et al.
Advances in Visual Computing - 16th International Symposium, ISVC 2021, Proceedings. ed. / George Bebis; Vassilis Athitsos; Tong Yan; Manfred Lau; Frederick Li; Conglei Shi; Xiaoru Yuan; Christos Mousas; Gerd Bruder. Springer Science and Business Media Deutschland GmbH, 2021. p. 53-64 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 13018 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Zhou, B, Mohammadi, F, Lim, JS, Forouzesh, N, Ghasemzadeh, H & Amini, N 2021, Analysis of Macular Thickness Deviation Maps for Diagnosis of Glaucoma. in G Bebis, V Athitsos, T Yan, M Lau, F Li, C Shi, X Yuan, C Mousas & G Bruder (eds), Advances in Visual Computing - 16th International Symposium, ISVC 2021, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 13018 LNCS, Springer Science and Business Media Deutschland GmbH, pp. 53-64, 16th International Symposium on Visual Computing, ISVC 2021, Virtual Online, 10/4/21. https://doi.org/10.1007/978-3-030-90436-4_5

Zhou B, Mohammadi F, Lim JS, Forouzesh N, Ghasemzadeh H, Amini N. Analysis of Macular Thickness Deviation Maps for Diagnosis of Glaucoma. In Bebis G, Athitsos V, Yan T, Lau M, Li F, Shi C, Yuan X, Mousas C, Bruder G, editors, Advances in Visual Computing - 16th International Symposium, ISVC 2021, Proceedings. Springer Science and Business Media Deutschland GmbH. 2021. p. 53-64. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-030-90436-4_5

Zhou, Bingnan ; Mohammadi, Farnaz ; Lim, Jung S. et al. / Analysis of Macular Thickness Deviation Maps for Diagnosis of Glaucoma. Advances in Visual Computing - 16th International Symposium, ISVC 2021, Proceedings. editor / George Bebis ; Vassilis Athitsos ; Tong Yan ; Manfred Lau ; Frederick Li ; Conglei Shi ; Xiaoru Yuan ; Christos Mousas ; Gerd Bruder. Springer Science and Business Media Deutschland GmbH, 2021. pp. 53-64 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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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 = "Bingnan Zhou and Farnaz Mohammadi and Lim, {Jung S.} and Negin Forouzesh and Hassan Ghasemzadeh and Navid Amini",

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AB - 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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Analysis of Macular Thickness Deviation Maps for Diagnosis of Glaucoma

Abstract

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