Correction propagation for user-assisted optical coherence tomography segmentation: general framework and application to Bruch’s membrane segmentation
Name
boe-11-5-2830.pdf
Description
Published version
Size
1.77 MB
Format
Adobe PDF
Checksum (MD5)
a3881480fe4cb218e1b438fc20c92488
Author(s)
Stromer, Daniel Johann
Moult, Eric Michael
Chen, Siyu
Fujimoto, James G
Date Issued
May 2020
Journal
Biomedical Optics Express
Publisher
The Optical Society
Citation
Stromer, Daniel et al. “Correction propagation for user-assisted optical coherence tomography segmentation: general framework and application to Bruch’s membrane segmentation.” Biomedical Optics Express, 11, 5 (May 2020): 392759 © 2020 The Author(s)
Version
Final published version
Abstract
Optical coherence tomography (OCT) is a commonly used ophthalmic imaging modality. While OCT has traditionally been viewed cross-sectionally (i.e., as a sequence of B-scans), higher A-scan rates have increased interest in en face OCT visualization and analysis. The recent clinical introduction of OCT angiography (OCTA) has further spurred this interest, with chorioretinal OCTA being predominantly displayed via en face projections. Although en face visualization and quantitation are natural for many retinal features (e.g., drusen and vasculature), it requires segmentation. Because manual segmentation of volumetric OCT data is prohibitively laborious in many settings, there has been significant research and commercial interest in developing automatic segmentation algorithms. While these algorithms have achieved impressive results, the variability of image qualities and the variety of ocular pathologies cause even the most robust automatic segmentation algorithms to err. In this study, we develop a user-assisted segmentation approach, complementary to fully-automatic methods, wherein correction propagation is used to reduce the burden of manually correcting automatic segmentations. The approach is evaluated for Bruch’s membrane segmentation in eyes with advanced age-related macular degeneration.
MIT Department
Massachusetts Institute of Technology. Research Laboratory of Electronics
Massachusetts Institute of Technology. Institute for Medical Engineering & Science
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
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Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.
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DOI of Published Version
https://doi.org/10.1364/BOE.392759
