Automated segmentation of the optic disc from stereo color photographs using physiologically plausible features.

Automated segmentation of the optic disc from stereo color photographs using physiologically plausible features. Research Abstract Details 

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Automated segmentation of the optic disc from stereo color photographs using physiologically plausible features. Abstract Text:

Michael D ,Wallace L M Alward,Emily C Greenlee,Lesya Shuba,Chan Y Kim,John H Fingert,Young H Kwon,

PURPOSE: To evaluate a novel automated segmentation algorithm for cup-to-disc segmentation from stereo color photographs of patients with glaucoma for the measurement of glaucoma progression. METHODS: Stereo color photographs of the optic disc were obtained by using a fixed stereo-base fundus camera in 58 eyes of 58 patients with suspected or open-angle glaucoma. Manual planimetry was performed by three glaucoma faculty members to delineate a reference standard rim and cup segmentation of all stereo pairs and by three glaucoma fellows as well. Pixel feature classification was evaluated on the stereo pairs and corresponding reference standard, by using feature computation based on simulation of photoreceptor color opponency and visual cortex simple and complex cells. An optimal subset of 12 features was used to segment all pixels in all stereo pairs, and the percentage of pixels assigned the correct class and linear cup-to-disc ratio (LCDR) estimates of the glaucoma fellows and the algorithm were compared to the reference standard. RESULTS: The algorithm was able to assign cup, rim, and background correctly to 88% of all pixels. Correlations of the LCDR estimates of glaucoma fellows with those of the reference standard were 0.73 (95% CI, 0.58-0.83), 0.81 (95% CI, 0.70-0.89), and 0.86 (95% CI, 0.78-0.91), respectively, whereas the correlation of the algorithm with the reference standard was 0.93 (95% CI, 0.89-0.96; n = 58). CONCLUSIONS: The pixel feature classification algorithm allows objective segmentation of the optic disc from conventional color stereo photographs automatically without human input. The performance of the disc segmentation and LCDR calculation of the algorithm was comparable to that of glaucoma fellows in training and is promising for objective evaluation of optic disc cupping.

Automated segmentation of the optic disc from stereo color photographs using physiologically plausible features. Publishing Authors By Initials

MD ,WL Alward,EC Greenlee,L Shuba,CY Kim,JH Fingert,YH Kwon,

For similar diagnosis: diagnostic techniques and procedures: diagnostic imaging: photography research abstracts see: diagnosis: diagnostic techniques and procedures: diagnostic imaging: photography research

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Automated segmentation of the optic disc from stereo color photographs using physiologically plausible features. Journal Published:

PUBLICATION TYPE: Research Support, U.S. Gov't,

Journal: Investigative ophthalmology & visual science

VOLUME: 48

Page Numbers: 1665-73

Journal Abbreviation: Invest. Ophthalmol. Vis. Sci.

ISSN: 0146-0404

DAY: 3

MONTH: Apr

YEAR: 2007

Automated segmentation of the optic disc from stereo color photographs using physiologically plausible features. Information

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LANGUAGE: eng

NlmUniqueID: 7703701

Automated segmentation of the optic disc from stereo color photographs using physiologically plausible features. Keywords Mesh Terms:

KEYWORDS: Photography

MESH TERMS: methods

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Grant and Affiliation Information for Automated segmentation of the optic disc from stereo color photographs using physiologically plausible features.

AFFILIATION: Department of Ophthalmology and Visual Sciences, University of Iowa Hospitals and Clinics, 200 Hawkins Drive, Iowa City, IA 52242, USA. michael-abramoff@uiowa.edu

Country: United States

AGENCY: United States NEI

GRANT: R01 EY 017066

ACRONYM: EY

MEDLINETA: Invest Ophthalmol Vis Sci

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