Paper
14 February 2012 Incorporation of texture-based features in optimal graph-theoretic approach with application to the 3D segmentation of intraretinal surfaces in SD-OCT volumes
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Abstract
While efficient graph-theoretic approaches exist for the optimal (with respect to a cost function) and simultaneous segmentation of multiple surfaces within volumetric medical images, the appropriate design of cost functions remains an important challenge. Previously proposed methods have used simple cost functions or optimized a combination of the same, but little has been done to design cost functions using learned features from a training set, in a less biased fashion. Here, we present a method to design cost functions for the simultaneous segmentation of multiple surfaces using the graph-theoretic approach. Classified texture features were used to create probability maps, which were incorporated into the graph-search approach. The efficiency of such an approach was tested on 10 optic nerve head centered optical coherence tomography (OCT) volumes obtained from 10 subjects that presented with glaucoma. The mean unsigned border position error was computed with respect to the average of manual tracings from two independent observers and compared to our previously reported results. A significant improvement was noted in the overall means which reduced from 9.25 ± 4.03μm to 6.73 ± 2.45μm (p < 0.01) and is also comparable with the inter-observer variability of 8.85 ± 3.85μm.
© (2012) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Bhavna J. Antony, Michael D. Abràmoff, Milan Sonka, Young H. Kwon, and Mona K. Garvin "Incorporation of texture-based features in optimal graph-theoretic approach with application to the 3D segmentation of intraretinal surfaces in SD-OCT volumes", Proc. SPIE 8314, Medical Imaging 2012: Image Processing, 83141G (14 February 2012); https://doi.org/10.1117/12.911491
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Cited by 7 scholarly publications.
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KEYWORDS
Image segmentation

Optical coherence tomography

Medical imaging

Head

Optic nerve

3D applications

3D image processing

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