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Incorporation of regional information in optimal 3-D graph search with application for intraretinal layer segmentation of optical coherence tomography images
Conference proceeding

Incorporation of regional information in optimal 3-D graph search with application for intraretinal layer segmentation of optical coherence tomography images

Mona Haeker, Xiaodong Wu, Michael Abràmoff, Randy Kardon and Milan Sonka
Information processing in medical imaging : proceedings of the ... conference, Vol.20, pp.607-618
2007
DOI: 10.1007/978-3-540-73273-0_50
PMID: 17633733

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Abstract

We present a method for the incorporation of regional image information in a 3-D graph-theoretic approach for optimal multiple surface segmentation. By transforming the multiple surface segmentation task into finding a minimum-cost closed set in a vertex-weighted graph, the optimal set of feasible surfaces with respect to an objective function can be found. In the past, this family of graph search applications only used objective functions which incorporated "on-surface" costs. Here, novel "in-region" costs are incorporated. Our new approach is applied to the segmentation of seven intraretinal layer surfaces of 24 3-D macular optical coherence tomography images from 12 subjects. Compared to an expert-defined independent standard, unsigned border positioning errors are comparable to the inter-observer variability (7.8 +/- 5.0 microm and 8.1 +/- 3.6 microm, respectively).
Algorithms Reproducibility of Results Retina - cytology Artificial Intelligence Humans Image Interpretation, Computer-Assisted - methods Sensitivity and Specificity Imaging, Three-Dimensional - methods Image Enhancement - methods Retinoscopy - methods Tomography, Optical Coherence - methods Pattern Recognition, Automated - methods

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