Segmentation techniques for computer-aided diagnosis of glaucoma: A review

Sumaiya Pathan; Preetham Kumar; Radhika M. Pai

doi:10.1007/978-981-10-8569-7_18

Segmentation techniques for computer-aided diagnosis of glaucoma: A review

Sumaiya Pathan, Preetham Kumar, Radhika M. Pai

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

2 Citations (Scopus)

Abstract

Glaucoma is an eye disease in which the optic nerve head (ONH) is damaged, leading to irreversible loss of vision. Vision loss due to glaucoma can be prevented only if it is detected at an early stage. Early diagnosis of glaucoma is possible by measuring the level of intra-ocular pressure (IOP) and the amount of neuro-retinal rim (NRR) area loss. The diagnosis accuracy depends on the experience and domain knowledge of the ophthalmologist. Hence, automated extraction of features from the retinal fundus images can play a major role for screening of glaucoma. The main aim of this paper is to review the different segmentation algorithms used to develop a computer-aided diagnostic (CAD) system for the detection of glaucoma from fundus images, and additionally, the future work is also highlighted.

Original language	English
Title of host publication	Advances in Machine Learning and Data Science - Recent Achievements and Research Directives
Publisher	Springer Verlag
Pages	163-173
Number of pages	11
ISBN (Print)	9789811085680
DOIs	https://doi.org/10.1007/978-981-10-8569-7_18
Publication status	Published - 01-01-2018
Event	1st International conference on Latest Advances in Machine learning and Data Science, LAMDA 2017 - Goa, India Duration: 25-10-2017 → 27-10-2017

Publication series

Name	Advances in Intelligent Systems and Computing
Volume	705
ISSN (Print)	2194-5357

Conference

Conference	1st International conference on Latest Advances in Machine learning and Data Science, LAMDA 2017
Country/Territory	India
City	Goa
Period	25-10-17 → 27-10-17

All Science Journal Classification (ASJC) codes

Control and Systems Engineering
Computer Science(all)

Access to Document

10.1007/978-981-10-8569-7_18

Cite this

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title = "Segmentation techniques for computer-aided diagnosis of glaucoma: A review",

abstract = "Glaucoma is an eye disease in which the optic nerve head (ONH) is damaged, leading to irreversible loss of vision. Vision loss due to glaucoma can be prevented only if it is detected at an early stage. Early diagnosis of glaucoma is possible by measuring the level of intra-ocular pressure (IOP) and the amount of neuro-retinal rim (NRR) area loss. The diagnosis accuracy depends on the experience and domain knowledge of the ophthalmologist. Hence, automated extraction of features from the retinal fundus images can play a major role for screening of glaucoma. The main aim of this paper is to review the different segmentation algorithms used to develop a computer-aided diagnostic (CAD) system for the detection of glaucoma from fundus images, and additionally, the future work is also highlighted.",

author = "Sumaiya Pathan and Preetham Kumar and Pai, {Radhika M.}",

year = "2018",

month = jan,

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doi = "10.1007/978-981-10-8569-7_18",

language = "English",

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series = "Advances in Intelligent Systems and Computing",

publisher = "Springer Verlag",

pages = "163--173",

booktitle = "Advances in Machine Learning and Data Science - Recent Achievements and Research Directives",

address = "Germany",

note = "1st International conference on Latest Advances in Machine learning and Data Science, LAMDA 2017 ; Conference date: 25-10-2017 Through 27-10-2017",

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Pathan, S , Kumar, P & Pai, RM 2018, Segmentation techniques for computer-aided diagnosis of glaucoma: A review. in Advances in Machine Learning and Data Science - Recent Achievements and Research Directives. Advances in Intelligent Systems and Computing, vol. 705, Springer Verlag, pp. 163-173, 1st International conference on Latest Advances in Machine learning and Data Science, LAMDA 2017, Goa, India, 25-10-17. https://doi.org/10.1007/978-981-10-8569-7_18

Segmentation techniques for computer-aided diagnosis of glaucoma: A review. / Pathan, Sumaiya ; Kumar, Preetham ; Pai, Radhika M.
Advances in Machine Learning and Data Science - Recent Achievements and Research Directives. Springer Verlag, 2018. p. 163-173 (Advances in Intelligent Systems and Computing; Vol. 705).

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

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T1 - Segmentation techniques for computer-aided diagnosis of glaucoma

T2 - 1st International conference on Latest Advances in Machine learning and Data Science, LAMDA 2017

AU - Pathan, Sumaiya

AU - Kumar, Preetham

AU - Pai, Radhika M.

PY - 2018/1/1

Y1 - 2018/1/1

N2 - Glaucoma is an eye disease in which the optic nerve head (ONH) is damaged, leading to irreversible loss of vision. Vision loss due to glaucoma can be prevented only if it is detected at an early stage. Early diagnosis of glaucoma is possible by measuring the level of intra-ocular pressure (IOP) and the amount of neuro-retinal rim (NRR) area loss. The diagnosis accuracy depends on the experience and domain knowledge of the ophthalmologist. Hence, automated extraction of features from the retinal fundus images can play a major role for screening of glaucoma. The main aim of this paper is to review the different segmentation algorithms used to develop a computer-aided diagnostic (CAD) system for the detection of glaucoma from fundus images, and additionally, the future work is also highlighted.

AB - Glaucoma is an eye disease in which the optic nerve head (ONH) is damaged, leading to irreversible loss of vision. Vision loss due to glaucoma can be prevented only if it is detected at an early stage. Early diagnosis of glaucoma is possible by measuring the level of intra-ocular pressure (IOP) and the amount of neuro-retinal rim (NRR) area loss. The diagnosis accuracy depends on the experience and domain knowledge of the ophthalmologist. Hence, automated extraction of features from the retinal fundus images can play a major role for screening of glaucoma. The main aim of this paper is to review the different segmentation algorithms used to develop a computer-aided diagnostic (CAD) system for the detection of glaucoma from fundus images, and additionally, the future work is also highlighted.

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ER -

Segmentation techniques for computer-aided diagnosis of glaucoma: A review

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