28 February 2009 3-D segmentation of the rim and cup in spectral-domain optical coherence tomography volumes of the optic nerve head
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Proceedings Volume 7262, Medical Imaging 2009: Biomedical Applications in Molecular, Structural, and Functional Imaging; 72622D (2009); doi: 10.1117/12.811315
Event: SPIE Medical Imaging, 2009, Lake Buena Vista (Orlando Area), Florida, United States
Abstract
Glaucoma is a group of diseases which can cause vision loss and blindness due to gradual damage to the optic nerve. The ratio of the optic disc cup to the optic disc is an important structural indicator for assessing the presence of glaucoma. The purpose of this study is to develop and evaluate a method which can segment the optic disc cup and neuroretinal rim in spectral-domain OCT scans centered on the optic nerve head. Our method starts by segmenting 3 intraretinal surfaces using a fast multiscale 3-D graph search method. Based on one of the segmented surfaces, the retina of the OCT volume is flattened to have a consistent shape across scans and patients. Selected features derived from OCT voxel intensities and intraretinal surfaces were used to train a k-NN classifier that can determine which A-scans in the OCT volume belong to the background, optic disc cup and neuroretinal rim. Through 3-fold cross validation with a training set of 20 optic nerve head-centered OCT scans (10 right eye scans and 10 left eye scans from 10 glaucoma patients) and a testing set of 10 OCT scans (5 right eye scans and 5 left eye scans from 5 different glaucoma patients), segmentation results of the optic disc cup and rim for all 30 OCT scans were obtained. The average unsigned errors of the optic disc cup and rim were 1.155 ± 1.391 pixels (0.035 ± 0.042 mm) and 1.295 ± 0.816 pixels (0.039 ± 0.024 mm), respectively.
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Kyungmoo Lee, Meindert Niemeijer, Mona K. Garvin, Young H. Kwon, Milan Sonka, Michael D. Abràmoff, "3-D segmentation of the rim and cup in spectral-domain optical coherence tomography volumes of the optic nerve head", Proc. SPIE 7262, Medical Imaging 2009: Biomedical Applications in Molecular, Structural, and Functional Imaging, 72622D (28 February 2009); doi: 10.1117/12.811315; https://doi.org/10.1117/12.811315
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KEYWORDS
Optical coherence tomography

Image segmentation

Optic nerve

Eye

Photography

Head

Feature selection

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