ARGALI- An automatic cup-to-disc ratio measurement system for Glaucoma detection and analysis framework

J. Liu; D. W.K. Wong; J. H. Lim; H. Li; N. M. Tan; T. Y. Wong

doi:10.1117/12.810956

ARGALI- An automatic cup-to-disc ratio measurement system for Glaucoma detection and analysis framework

J. Liu, D. W.K. Wong, J. H. Lim, H. Li, N. M. Tan, T. Y. Wong

Research output: Chapter in Book/Conference proceeding › Conference contribution › peer-review

35 Citations (Scopus)

Abstract

Glaucoma is an irreversible ocular disease leading to permanent blindness. However, early detection can be effective in slowing or halting the progression of the disease. Physiologically, glaucoma progression is quantified by increased excavation of the optic cup. This progression can be quantified in retinal fundus images via the optic cup to disc ratio (CDR), since in increased glaucomatous neuropathy, the relative size of the optic cup to the optic disc is increased. The ARGALI framework constitutes of various segmentation approaches employing level set, color intensity thresholds and ellipse fitting for the extraction of the optic cup and disc from retinal images as preliminary steps. Following this, different combinations of the obtained results are then utilized to calculate the corresponding CDR values. The individual results are subsequently fused using a neural network. The learning function of the neural network is trained with a set of 100 retinal images For testing, a separate set 40 images is then used to compare the obtained CDR against a clinically graded CDR, and it is shown that the neural network-based result performs better than the individual components, with 96% of the results within intra-observer variability. The results indicate good promise for the further development of ARGALI as a tool for the early detection of glaucoma

Original language	English
Title of host publication	Medical Imaging 2009
Subtitle of host publication	Computer-Aided Diagnosis
DOIs	https://doi.org/10.1117/12.810956
Publication status	Published - 2009
Externally published	Yes
Event	Medical Imaging 2009: Computer-Aided Diagnosis - Lake Buena Vista, FL, United States Duration: 10 Feb 2009 → 12 Feb 2009

Publication series

Name	Progress in Biomedical Optics and Imaging - Proceedings of SPIE
Volume	7260
ISSN (Print)	1605-7422

Conference

Conference	Medical Imaging 2009: Computer-Aided Diagnosis
Country/Territory	United States
City	Lake Buena Vista, FL
Period	10/02/09 → 12/02/09

Keywords

Cup-to-disc ratio
Glaucoma
Level-set
Neural network

ASJC Scopus subject areas

Electronic, Optical and Magnetic Materials
Biomaterials
Atomic and Molecular Physics, and Optics
Radiology Nuclear Medicine and imaging

Access to Document

10.1117/12.810956

Cite this

@inproceedings{eef0922011c940a4b0ec056f59691675,

title = "ARGALI- An automatic cup-to-disc ratio measurement system for Glaucoma detection and analysis framework",

abstract = "Glaucoma is an irreversible ocular disease leading to permanent blindness. However, early detection can be effective in slowing or halting the progression of the disease. Physiologically, glaucoma progression is quantified by increased excavation of the optic cup. This progression can be quantified in retinal fundus images via the optic cup to disc ratio (CDR), since in increased glaucomatous neuropathy, the relative size of the optic cup to the optic disc is increased. The ARGALI framework constitutes of various segmentation approaches employing level set, color intensity thresholds and ellipse fitting for the extraction of the optic cup and disc from retinal images as preliminary steps. Following this, different combinations of the obtained results are then utilized to calculate the corresponding CDR values. The individual results are subsequently fused using a neural network. The learning function of the neural network is trained with a set of 100 retinal images For testing, a separate set 40 images is then used to compare the obtained CDR against a clinically graded CDR, and it is shown that the neural network-based result performs better than the individual components, with 96% of the results within intra-observer variability. The results indicate good promise for the further development of ARGALI as a tool for the early detection of glaucoma",

keywords = "Cup-to-disc ratio, Glaucoma, Level-set, Neural network",

author = "J. Liu and Wong, {D. W.K.} and Lim, {J. H.} and H. Li and Tan, {N. M.} and Wong, {T. Y.}",

year = "2009",

doi = "10.1117/12.810956",

language = "English",

isbn = "9780819475114",

series = "Progress in Biomedical Optics and Imaging - Proceedings of SPIE",

booktitle = "Medical Imaging 2009",

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Liu, J, Wong, DWK, Lim, JH, Li, H, Tan, NM & Wong, TY 2009, ARGALI- An automatic cup-to-disc ratio measurement system for Glaucoma detection and analysis framework. in Medical Imaging 2009: Computer-Aided Diagnosis., 72603K, Progress in Biomedical Optics and Imaging - Proceedings of SPIE, vol. 7260, Medical Imaging 2009: Computer-Aided Diagnosis, Lake Buena Vista, FL, United States, 10/02/09. https://doi.org/10.1117/12.810956

ARGALI- An automatic cup-to-disc ratio measurement system for Glaucoma detection and analysis framework. / Liu, J.; Wong, D. W.K.; Lim, J. H. et al.
Medical Imaging 2009: Computer-Aided Diagnosis. 2009. 72603K (Progress in Biomedical Optics and Imaging - Proceedings of SPIE; Vol. 7260).

Research output: Chapter in Book/Conference proceeding › Conference contribution › peer-review

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AU - Wong, T. Y.

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AB - Glaucoma is an irreversible ocular disease leading to permanent blindness. However, early detection can be effective in slowing or halting the progression of the disease. Physiologically, glaucoma progression is quantified by increased excavation of the optic cup. This progression can be quantified in retinal fundus images via the optic cup to disc ratio (CDR), since in increased glaucomatous neuropathy, the relative size of the optic cup to the optic disc is increased. The ARGALI framework constitutes of various segmentation approaches employing level set, color intensity thresholds and ellipse fitting for the extraction of the optic cup and disc from retinal images as preliminary steps. Following this, different combinations of the obtained results are then utilized to calculate the corresponding CDR values. The individual results are subsequently fused using a neural network. The learning function of the neural network is trained with a set of 100 retinal images For testing, a separate set 40 images is then used to compare the obtained CDR against a clinically graded CDR, and it is shown that the neural network-based result performs better than the individual components, with 96% of the results within intra-observer variability. The results indicate good promise for the further development of ARGALI as a tool for the early detection of glaucoma

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ER -

ARGALI- An automatic cup-to-disc ratio measurement system for Glaucoma detection and analysis framework

Abstract

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Keywords

ASJC Scopus subject areas

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