Open AccessAutomated layer segmentation of macular OCT images using dual-scale gradient information
Author(s) -
Qi Yang,
Charles Reisman,
Zhenguo Wang,
Y. Fukuma,
Masanori Hangai,
Nagahisa Yoshimura,
Atsuo Tomidokoro,
Makoto Araie,
Ali Raza,
Donald C. Hood,
Kinpui Chan
Publication year - 2010
Publication title -
optics express
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.394
H-Index - 271
ISSN - 1094-4087
DOI - 10.1364/oe.18.021293
Subject(s) - segmentation , optical coherence tomography , computer science , artificial intelligence , voxel , computer vision , image segmentation , pattern recognition (psychology) , optics , physics
A novel automated boundary segmentation algorithm is proposed for fast and reliable quantification of nine intra-retinal boundaries in optical coherence tomography (OCT) images. The algorithm employs a two-step segmentation schema based on gradient information in dual scales, utilizing local and complementary global gradient information simultaneously. A shortest path search is applied to optimize the edge selection. The segmentation algorithm was validated with independent manual segmentation and a reproducibility study. It demonstrates high accuracy and reproducibility in segmenting normal 3D OCT volumes. The execution time is about 16 seconds per volume (480x512x128 voxels). The algorithm shows potential for quantifying images from diseased retinas as well.