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Three-dimensional segmentation of fluid-associated abnormalities in retinal OCT: probability constrained graph-search-graph-cut
Journal article   Peer reviewed

Three-dimensional segmentation of fluid-associated abnormalities in retinal OCT: probability constrained graph-search-graph-cut

Xinjian Chen, Meindert Niemeijer, Li Zhang, Kyungmoo Lee, Michael D Abramoff and Milan Sonka
IEEE transactions on medical imaging, Vol.31(8), pp.1521-1531
08/2012
DOI: 10.1109/TMI.2012.2191302
PMCID: PMC3659794
PMID: 22453610

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Abstract

An automated method is reported for segmenting 3-D fluid-associated abnormalities in the retina, so-called symptomatic exudate-associated derangements (SEAD), from 3-D OCT retinal images of subjects suffering from exudative age-related macular degeneration. In the first stage of a two-stage approach, retinal layers are segmented, candidate SEAD regions identified, and the retinal OCT image is flattened using a candidate-SEAD aware approach. In the second stage, a probability constrained combined graph search-graph cut method refines the candidate SEADs by integrating the candidate volumes into the graph cut cost function as probability constraints. The proposed method was evaluated on 15 spectral domain OCT images from 15 subjects undergoing intravitreal anti-VEGF injection treatment. Leave-one-out evaluation resulted in a true positive volume fraction (TPVF), false positive volume fraction (FPVF) and relative volume difference ratio (RVDR) of 86.5%, 1.7%, and 12.8%, respectively. The new graph cut-graph search method significantly outperformed both the traditional graph cut and traditional graph search approaches (p < 0.01, p < 0.04) and has the potential to improve clinical management of patients with choroidal neovascularization due to exudative age-related macular degeneration.
Algorithms Reproducibility of Results Humans Imaging, Three-Dimensional - methods Tomography, Optical Coherence - methods Retina - pathology Exudates and Transudates Macular Degeneration - pathology

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