Automatic segmentation of the choroid in enhanced depth imaging optical coherence tomography images
Tun, Tin Aung
Date of Issue2013
School of Electrical and Electronic Engineering
Enhanced Depth Imaging (EDI) optical coherence tomography (OCT) provides high-definition cross-sectional images of the choroid in vivo, and hence is used in many clinical studies. However, the quantification of the choroid depends on the manual labelings of two boundaries, Bruch’s membrane and the choroidal-scleral interface. This labeling process is tedious and subjective of inter-observer differences, hence, automatic segmentation of the choroid layer is highly desirable. In this paper, we present a fast and accurate algorithm that could segment the choroid automatically. Bruch’s membrane is detected by searching the pixel with the biggest gradient value above the retinal pigment epithelium (RPE) and the choroidal-scleral interface is delineated by finding the shortest path of the graph formed by valley pixels using Dijkstra’s algorithm. The experiments comparing automatic segmentation results with the manual labelings are conducted on 45 EDI-OCT images and the average of Dice’s Coefficient is 90.5%, which shows good consistency of the algorithm with the manual labelings. The processing time for each image is about 1.25 seconds.
DRNTU::Engineering::Electrical and electronic engineering
Biomedical optics express
© 2013 Optical Society of America. This paper was published in Biomedical Optics Express and is made available as an electronic reprint (preprint) with permission of Optical Society of America. The paper can be found at the following official DOI: [http://dx.doi.org/10.1364/BOE.4.000397]. One print or electronic copy may be made for personal use only. Systematic or multiple reproduction, distribution to multiple locations via electronic or other means, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper is prohibited and is subject to penalties under law.