Automated boundary detection of the optic disc and layer segmentation of the peripapillary retina in volumetric structural and angiographic optical coherence tomography

Research output: Research - peer-reviewArticle

Abstract

To improve optic disc boundary detection and peripapillary retinal layer segmentation, we propose an automated approach for structural and angiographic optical coherence tomography. The algorithm was performed on radial cross-sectional B-scans. The disc boundary was detected by searching for the position of Bruch’s membrane opening, and retinal layer boundaries were detected using a dynamic programming-based graph search algorithm on each B-scan without the disc region. A comparison of the disc boundary using our method with that determined by manual delineation showed good accuracy, with an average Dice similarity coefficient ≥0.90 in healthy eyes and eyes with diabetic retinopathy and glaucoma. The layer segmentation accuracy in the same cases was on average less than one pixel (3.13 μm).

LanguageEnglish (US)
Article number#282471
Pages1306-1318
Number of pages13
JournalBiomedical Optics Express
Volume8
Issue number3
DOIs
StatePublished - Mar 1 2017

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retina
edge detection
tomography
optics
Optic Disk
Optical Coherence Tomography
Retina
Bruch Membrane
Diabetic Retinopathy
Glaucoma
glaucoma
dynamic programming
delineation
boundary layers
pixels
membranes
coefficients

ASJC Scopus subject areas

  • Biotechnology
  • Atomic and Molecular Physics, and Optics

Cite this

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abstract = "To improve optic disc boundary detection and peripapillary retinal layer segmentation, we propose an automated approach for structural and angiographic optical coherence tomography. The algorithm was performed on radial cross-sectional B-scans. The disc boundary was detected by searching for the position of Bruch’s membrane opening, and retinal layer boundaries were detected using a dynamic programming-based graph search algorithm on each B-scan without the disc region. A comparison of the disc boundary using our method with that determined by manual delineation showed good accuracy, with an average Dice similarity coefficient ≥0.90 in healthy eyes and eyes with diabetic retinopathy and glaucoma. The layer segmentation accuracy in the same cases was on average less than one pixel (3.13 μm).",
author = "Pengxiao Zang and Gao, {Simon S.} and Hwang, {Thomas S.} and Flaxel, {Christina J.} and Wilson, {David J.} and Morrison, {John C.} and David Huang and Dengwang Li and Yali Jia",
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AU - Hwang,Thomas S.

AU - Flaxel,Christina J.

AU - Wilson,David J.

AU - Morrison,John C.

AU - Huang,David

AU - Li,Dengwang

AU - Jia,Yali

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AB - To improve optic disc boundary detection and peripapillary retinal layer segmentation, we propose an automated approach for structural and angiographic optical coherence tomography. The algorithm was performed on radial cross-sectional B-scans. The disc boundary was detected by searching for the position of Bruch’s membrane opening, and retinal layer boundaries were detected using a dynamic programming-based graph search algorithm on each B-scan without the disc region. A comparison of the disc boundary using our method with that determined by manual delineation showed good accuracy, with an average Dice similarity coefficient ≥0.90 in healthy eyes and eyes with diabetic retinopathy and glaucoma. The layer segmentation accuracy in the same cases was on average less than one pixel (3.13 μm).

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