Exploiting texture information in diagnosing Glaucoma

E. T. Gormus; N. Anantrasirichai; M. Bundy; I. Erchova; N White; J. Fergusson; J Morgan; L. B. Nicholson; A. Achim

doi:10.1109/SIU.2017.7960648

Exploiting texture information in diagnosing Glaucoma

E. T. Gormus^*, N. Anantrasirichai, M. Bundy, I. Erchova, N White, J. Fergusson, J Morgan, L. B. Nicholson, A. Achim

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference Contribution (Conference Proceeding)

1 Citation (Scopus)

Abstract

The most common cause of blindness in the world by far is known to be the Glaucoma condition. The increase in the ratio of cup to the disc area and the thinning of retinal layers are the most common symptoms of Glaucoma. Functional and structural features of the eye should be examined in order to distinguish an eye with Glaucoma from a healthy eye. In this study, the texture information in Optical Coherence Tomography (OCT) images, which is one of the functional features is investigated to get the most distinguishing characteristic texture patterns in retina layers. First, sample areas are extracted from 4 main region around the fovea using a systematic approach and calculated the texture features for each area one by one. After this step SVM classifier is exploited to find the features which can impact the diagnosis of Glaucoma condition. This analysis is useful to guide the scientists to diagnose glaucoma where the thickness information is not available or at the beginning of the Glaucoma when thinning is not started yet.

Original language	English
Title of host publication	2017 25th Signal Processing and Communications Applications Conference, SIU 2017
Subtitle of host publication	Proceedings of a meeting held 15-18 May 2017, Antalya, Turkey
Publisher	Institute of Electrical and Electronics Engineers (IEEE)
Number of pages	4
ISBN (Electronic)	9781509064946
ISBN (Print)	9781509064953
DOIs	https://doi.org/10.1109/SIU.2017.7960648
Publication status	Published - Aug 2017
Event	25th Signal Processing and Communications Applications Conference, SIU 2017 - Antalya, Turkey Duration: 15 May 2017 → 18 May 2017

Conference

Conference	25th Signal Processing and Communications Applications Conference, SIU 2017
Country/Territory	Turkey
City	Antalya
Period	15/05/17 → 18/05/17

Bibliographical note

Original title in Turkish: Doku Bilgisinin Glokom Hastaliǧinin Teşshis Edilmesinde Kullanilmasi

Keywords

Classification
Feature Selection
Gloucoma
Optical Coherence Tomography (OCT)
Support Vector Machines (SVM)
Texture Analysis

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Gormus, E. T., Anantrasirichai, N., Bundy, M., Erchova, I., White, N., Fergusson, J., Morgan, J., Nicholson, L. B., & Achim, A. (2017). Exploiting texture information in diagnosing Glaucoma. In 2017 25th Signal Processing and Communications Applications Conference, SIU 2017: Proceedings of a meeting held 15-18 May 2017, Antalya, Turkey Article 7960648 Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/SIU.2017.7960648

@inproceedings{dece26d6c9d041629ddfbd4c082a72a7,

title = "Exploiting texture information in diagnosing Glaucoma",

abstract = "The most common cause of blindness in the world by far is known to be the Glaucoma condition. The increase in the ratio of cup to the disc area and the thinning of retinal layers are the most common symptoms of Glaucoma. Functional and structural features of the eye should be examined in order to distinguish an eye with Glaucoma from a healthy eye. In this study, the texture information in Optical Coherence Tomography (OCT) images, which is one of the functional features is investigated to get the most distinguishing characteristic texture patterns in retina layers. First, sample areas are extracted from 4 main region around the fovea using a systematic approach and calculated the texture features for each area one by one. After this step SVM classifier is exploited to find the features which can impact the diagnosis of Glaucoma condition. This analysis is useful to guide the scientists to diagnose glaucoma where the thickness information is not available or at the beginning of the Glaucoma when thinning is not started yet.",

keywords = "Classification, Feature Selection, Gloucoma, Optical Coherence Tomography (OCT), Support Vector Machines (SVM), Texture Analysis",

author = "Gormus, {E. T.} and N. Anantrasirichai and M. Bundy and I. Erchova and N White and J. Fergusson and J Morgan and Nicholson, {L. B.} and A. Achim",

note = "Original title in Turkish: Doku Bilgisinin Glokom Hastaliǧinin Te{\c s}shis Edilmesinde Kullanilmasi; 25th Signal Processing and Communications Applications Conference, SIU 2017 ; Conference date: 15-05-2017 Through 18-05-2017",

year = "2017",

month = aug,

doi = "10.1109/SIU.2017.7960648",

language = "English",

isbn = "9781509064953",

booktitle = "2017 25th Signal Processing and Communications Applications Conference, SIU 2017",

publisher = "Institute of Electrical and Electronics Engineers (IEEE)",

address = "United States",

}

Gormus, ET, Anantrasirichai, N, Bundy, M, Erchova, I, White, N, Fergusson, J, Morgan, J, Nicholson, LB & Achim, A 2017, Exploiting texture information in diagnosing Glaucoma. in 2017 25th Signal Processing and Communications Applications Conference, SIU 2017: Proceedings of a meeting held 15-18 May 2017, Antalya, Turkey., 7960648, Institute of Electrical and Electronics Engineers (IEEE), 25th Signal Processing and Communications Applications Conference, SIU 2017, Antalya, Turkey, 15/05/17. https://doi.org/10.1109/SIU.2017.7960648

Exploiting texture information in diagnosing Glaucoma. / Gormus, E. T.; Anantrasirichai, N.; Bundy, M. et al.
2017 25th Signal Processing and Communications Applications Conference, SIU 2017: Proceedings of a meeting held 15-18 May 2017, Antalya, Turkey. Institute of Electrical and Electronics Engineers (IEEE), 2017. 7960648.

Research output: Chapter in Book/Report/Conference proceeding › Conference Contribution (Conference Proceeding)

TY - GEN

T1 - Exploiting texture information in diagnosing Glaucoma

AU - Gormus, E. T.

AU - Anantrasirichai, N.

AU - Bundy, M.

AU - Erchova, I.

AU - White, N

AU - Fergusson, J.

AU - Morgan, J

AU - Nicholson, L. B.

AU - Achim, A.

N1 - Original title in Turkish: Doku Bilgisinin Glokom Hastaliǧinin Teşshis Edilmesinde Kullanilmasi

PY - 2017/8

Y1 - 2017/8

N2 - The most common cause of blindness in the world by far is known to be the Glaucoma condition. The increase in the ratio of cup to the disc area and the thinning of retinal layers are the most common symptoms of Glaucoma. Functional and structural features of the eye should be examined in order to distinguish an eye with Glaucoma from a healthy eye. In this study, the texture information in Optical Coherence Tomography (OCT) images, which is one of the functional features is investigated to get the most distinguishing characteristic texture patterns in retina layers. First, sample areas are extracted from 4 main region around the fovea using a systematic approach and calculated the texture features for each area one by one. After this step SVM classifier is exploited to find the features which can impact the diagnosis of Glaucoma condition. This analysis is useful to guide the scientists to diagnose glaucoma where the thickness information is not available or at the beginning of the Glaucoma when thinning is not started yet.

AB - The most common cause of blindness in the world by far is known to be the Glaucoma condition. The increase in the ratio of cup to the disc area and the thinning of retinal layers are the most common symptoms of Glaucoma. Functional and structural features of the eye should be examined in order to distinguish an eye with Glaucoma from a healthy eye. In this study, the texture information in Optical Coherence Tomography (OCT) images, which is one of the functional features is investigated to get the most distinguishing characteristic texture patterns in retina layers. First, sample areas are extracted from 4 main region around the fovea using a systematic approach and calculated the texture features for each area one by one. After this step SVM classifier is exploited to find the features which can impact the diagnosis of Glaucoma condition. This analysis is useful to guide the scientists to diagnose glaucoma where the thickness information is not available or at the beginning of the Glaucoma when thinning is not started yet.

KW - Classification

KW - Feature Selection

KW - Gloucoma

KW - Optical Coherence Tomography (OCT)

KW - Support Vector Machines (SVM)

KW - Texture Analysis

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U2 - 10.1109/SIU.2017.7960648

DO - 10.1109/SIU.2017.7960648

M3 - Conference Contribution (Conference Proceeding)

AN - SCOPUS:85026288884

SN - 9781509064953

BT - 2017 25th Signal Processing and Communications Applications Conference, SIU 2017

PB - Institute of Electrical and Electronics Engineers (IEEE)

T2 - 25th Signal Processing and Communications Applications Conference, SIU 2017

Y2 - 15 May 2017 through 18 May 2017

ER -

Gormus ET, Anantrasirichai N, Bundy M, Erchova I, White N, Fergusson J et al. Exploiting texture information in diagnosing Glaucoma. In 2017 25th Signal Processing and Communications Applications Conference, SIU 2017: Proceedings of a meeting held 15-18 May 2017, Antalya, Turkey. Institute of Electrical and Electronics Engineers (IEEE). 2017. 7960648 Epub 2017 Jun 29. doi: 10.1109/SIU.2017.7960648

Exploiting texture information in diagnosing Glaucoma

Abstract

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Bibliographical note

Keywords

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