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Proceedings Paper

Multimodal segmentation of optic disc and cup from stereo fundus and SD-OCT images
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Paper Abstract

Glaucoma is one of the major causes of blindness worldwide. One important structural parameter for the diagnosis and management of glaucoma is the cup-to-disc ratio (CDR), which tends to become larger as glaucoma progresses. While approaches exist for segmenting the optic disc and cup within fundus photographs, and more recently, within spectral-domain optical coherence tomography (SD-OCT) volumes, no approaches have been reported for the simultaneous segmentation of these structures within both modalities combined. In this work, a multimodal pixel-classification approach for the segmentation of the optic disc and cup within fundus photographs and SD-OCT volumes is presented. In particular, after segmentation of other important structures (such as the retinal layers and retinal blood vessels) and fundus-to-SD-OCT image registration, features are extracted from both modalities and a k-nearest-neighbor classification approach is used to classify each pixel as cup, rim, or background. The approach is evaluated on 70 multimodal image pairs from 35 subjects in a leave-10%-out fashion (by subject). A significant improvement in classification accuracy is obtained using the multimodal approach over that obtained from the corresponding unimodal approach (97.8% versus 95.2%; p < 0:05; paired t-test).

Paper Details

Date Published: 13 March 2013
PDF: 9 pages
Proc. SPIE 8669, Medical Imaging 2013: Image Processing, 86690O (13 March 2013); doi: 10.1117/12.2007010
Show Author Affiliations
Mohammad Saleh Miri, The Univ. of Iowa (United States)
Kyungmoo Lee, The Univ. of Iowa (United States)
Meindert Niemeijer, The Univ. of Iowa (United States)
Michael D. Abràmoff, The Univ. of Iowa (United States)
U.S. Dept. of Veterans Affairs (United States)
Young H. Kwon, The Univ. of Iowa (United States)
Mona K. Garvin, U.S. Dept. of Veterans Affairs (United States)
The Univ. of Iowa (United States)

Published in SPIE Proceedings Vol. 8669:
Medical Imaging 2013: Image Processing
Sebastien Ourselin; David R. Haynor, Editor(s)

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