Variance Reduction in a Dataset of Normal Macular Ganglion Cell Plus Inner Plexiform Layer Thickness Maps with Application to Glaucoma Diagnosis

Robert W Knighton; Giovanni Gregori; Donald L Budenz

doi:10.1167/iovs.12-9719

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Variance Reduction in a Dataset of Normal Macular Ganglion Cell Plus Inner Plexiform Layer Thickness Maps with Application to Glaucoma Diagnosis

Journal article

Open access

Peer reviewed

Variance Reduction in a Dataset of Normal Macular Ganglion Cell Plus Inner Plexiform Layer Thickness Maps with Application to Glaucoma Diagnosis

Robert W Knighton, Giovanni Gregori and Donald L Budenz

Investigative ophthalmology & visual science, Vol.53(7), pp.3653-3661

2012-06

DOI: https://doi.org/10.1167/iovs.12-9719

PMCID: PMC3406888

PMID: 22562512

Abstract

The ganglion cell layer of the normal macula forms an annular mound that differs among individuals mainly in diameter and thickness. This similarity in shape provides an opportunity for transformations that reduce the variance of normative databases for glaucoma diagnosis.

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Collaboration types: Domestic collaboration
Citation topics: 1 Clinical & Life Sciences; 1.36 Ophthalmology; 1.36.226 Glaucoma
Web Of Science research areas: Ophthalmology
ESI research areas: Clinical Medicine

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Details

Title: Variance Reduction in a Dataset of Normal Macular Ganglion Cell Plus Inner Plexiform Layer Thickness Maps with Application to Glaucoma Diagnosis
Creators: Robert W Knighton - Bascom Palmer Eye Institute, University of Miami Miller School of Medicine, Miami, Florida; and the
Giovanni Gregori - Bascom Palmer Eye Institute, University of Miami Miller School of Medicine, Miami, Florida; and the
Donald L Budenz - Department of Ophthalmology, University of North Carolina School of Medicine, Chapel Hill, North Carolina
Publication Details: Investigative ophthalmology & visual science, Vol.53(7), pp.3653-3661
Publisher: The Association for Research in Vision and Ophthalmology
Academic Unit: Miller School of Medicine; UMMG Department of Ophthalmology
Language: English
Resource Type: Journal article
PMID: 22562512
PMCID: PMC3406888
Record Identifier: 991031578751302976