User-guided segmentation for volumetric retinal optical coherence tomography images

Xin Yin; Jennifer R. Chao; Ruikang K. Wang

doi:10.1117/1.JBO.19.8.086020

22 August 2014 User-guided segmentation for volumetric retinal optical coherence tomography images

Xin Yin, Jennifer R. Chao, Ruikang K. Wang

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Journal of Biomedical Optics, Vol. 19, Issue 8, 086020 (August 2014). https://doi.org/10.1117/1.JBO.19.8.086020

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.

CC BY: © The Authors. Published by SPIE under a Creative Commons Attribution 4.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.

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Xin Yin, Jennifer R. Chao, and Ruikang K. Wang "User-guided segmentation for volumetric retinal optical coherence tomography images," Journal of Biomedical Optics 19(8), 086020 (22 August 2014). https://doi.org/10.1117/1.JBO.19.8.086020

Published: 22 August 2014

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