Intraretinal Layer Segmentation of Macular Optical Coherence Tomography Images Using Optimal 3-D Graph Search

M.K Garvin; M.D Abramoff; R Kardon; S.R Russell; Xiaodong Wu; M Sonka

doi:10.1109/TMI.2008.923966

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Intraretinal Layer Segmentation of Macular Optical Coherence Tomography Images Using Optimal 3-D Graph Search

Journal article

Open access

Intraretinal Layer Segmentation of Macular Optical Coherence Tomography Images Using Optimal 3-D Graph Search

M.K Garvin, M.D Abramoff, R Kardon, S.R Russell, Xiaodong Wu and M Sonka

IEEE Transactions on Medical Imaging, Vol.27(10), pp.1495-1505

10/2008

DOI: 10.1109/TMI.2008.923966

PMCID: PMC2614384

PMID: 18815101

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Abstract

Current techniques for segmenting macular optical coherence tomography (OCT) images have been 2-D in nature. Furthermore, commercially available OCT systems have only focused on segmenting a single layer of the retina, even though each intraretinal layer may be affected differently by disease. We report an automated approach for segmenting (anisotropic) 3-D macular OCT scans into five layers. Each macular OCT dataset consisted of six linear radial scans centered at the fovea. The six surfaces defining the five layers were identified on each 3-D composite image by transforming the segmentation task into that of finding a minimum-cost closed set in a geometric graph constructed from edge/regional information and a priori determined surface smoothness and interaction constraints. The method was applied to the macular OCT scans of 12 patients (24 3-D composite image datasets) with unilateral anterior ischemic optic neuropathy (AION). Using the average of three experts' tracings as a reference standard resulted in an overall mean unsigned border positioning error of 6.1 plusmn 2.9 mum, a result comparable to the interobserver variability (6.9 plusmn 3.3 mum).Our quantitative analysis of the automated segmentation results from AION subject data revealed that the inner retinal layer thickness for the affected eye was 24.1 mum (21%) smaller on average than for the unaffected eye (p < 0.001), supporting the need for segmenting the layers separately.

Oncology

Ophthalmology

Biomedical Engineering

Biomedical optical imaging

optical coherence tomography

Retina

Geometrical optics

3-D graph search

Image segmentation

Tomography

Cities and towns

segmentation

Medical diagnostic imaging

Biomedical imaging

Details

Title: Subtitle: Intraretinal Layer Segmentation of Macular Optical Coherence Tomography Images Using Optimal 3-D Graph Search
Creators: M.K Garvin - Dept. of Electr. & Comput. Eng. & the Dept. of Biomed. Eng., Iowa Univ., Iowa City, IA
M.D Abramoff
R Kardon
S.R Russell
Xiaodong Wu
M Sonka
Resource Type: Journal article
Publication Details: IEEE Transactions on Medical Imaging, Vol.27(10), pp.1495-1505
DOI: 10.1109/TMI.2008.923966
PMID: 18815101
PMCID: PMC2614384
NLM abbreviation: IEEE Trans Med Imaging
ISSN: 0278-0062
eISSN: 1558-254X
Publisher: IEEE
Language: English
Date published: 10/2008
Academic Unit: Roy J. Carver Department of Biomedical Engineering; Electrical and Computer Engineering; Iowa Neuroscience Institute; Radiation Oncology; Injury Prevention Research Center; Ophthalmology and Visual Sciences
Record Identifier: 9983806267002771

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