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Journal of Biomedical Optics • Open Access

User-guided segmentation for volumetric retinal optical coherence tomography images
Author(s): Xin Yin; Jennifer R. Chao; Ruikang K. Wang

Paper Abstract

Despite the existence of automatic segmentation techniques, trained graders still rely on manual segmentation to provide retinal layers and features from clinical optical coherence tomography (OCT) images for accurate measurements. To bridge the gap between this time-consuming need of manual segmentation and currently available automatic segmentation techniques, this paper proposes a user-guided segmentation method to perform the segmentation of retinal layers and features in OCT images. With this method, by interactively navigating three-dimensional (3-D) OCT images, the user first manually defines user-defined (or sketched) lines at regions where the retinal layers appear very irregular for which the automatic segmentation method often fails to provide satisfactory results. The algorithm is then guided by these sketched lines to trace the entire 3-D retinal layer and anatomical features by the use of novel layer and edge detectors that are based on robust likelihood estimation. The layer and edge boundaries are finally obtained to achieve segmentation. Segmentation of retinal layers in mouse and human OCT images demonstrates the reliability and efficiency of the proposed user-guided segmentation method.

Paper Details

Date Published: 22 August 2014
PDF: 10 pages
J. Biomed. Opt. 19(8) 086020 doi: 10.1117/1.JBO.19.8.086020
Published in: Journal of Biomedical Optics Volume 19, Issue 8
Show Author Affiliations
Xin Yin, Univ. of Washington (United States)
Jennifer R. Chao, Univ. of Washington (United States)
Ruikang K. Wang, Univ. of Washington (United States)

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