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Proceedings Paper

Automatic segmentation of canine retinal OCT using adaptive gradient enhancement and region growing
Author(s): Yufan He; Yankui Sun; Min Chen; Yuanjie Zheng; Hui Liu; Cecilia Leon; William Beltran; James C. Gee
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Paper Abstract

In recent years, several studies have shown that the canine retina model offers important insight for our understanding of human retinal diseases. Several therapies developed to treat blindness in such models have already moved onto human clinical trials, with more currently under development [1]. Optical coherence tomography (OCT) offers a high resolution imaging modality for performing in-vivo analysis of the retinal layers. However, existing algorithms for automatically segmenting and analyzing such data have been mostly focused on the human retina. As a result, canine retinal images are often still being analyzed using manual segmentations, which is a slow and laborious task. In this work, we propose a method for automatically segmenting 5 boundaries in canine retinal OCT. The algorithm employs the position relationships between different boundaries to adaptively enhance the gradient map. A region growing algorithm is then used on the enhanced gradient maps to find the five boundaries separately. The automatic segmentation was compared against manual segmentations showing an average absolute error of 5.82 ± 4.02 microns.

Paper Details

Date Published: 29 March 2016
PDF: 7 pages
Proc. SPIE 9788, Medical Imaging 2016: Biomedical Applications in Molecular, Structural, and Functional Imaging, 97881Q (29 March 2016); doi: 10.1117/12.2217186
Show Author Affiliations
Yufan He, Tsinghua Univ. (China)
Univ. of Pennsylvania (United States)
Yankui Sun, Tsinghua Univ. (China)
Min Chen, Univ. of Pennsylvania (United States)
Yuanjie Zheng, Univ. of Pennsylvania (United States)
Shandong Normal Univ. (China)
Hui Liu, Univ. of Pennsylvania (United States)
Cecilia Leon, Univ. of Pennsylvania (United States)
William Beltran, Univ. of Pennsylvania (United States)
James C. Gee, Univ. of Pennsylvania (United States)


Published in SPIE Proceedings Vol. 9788:
Medical Imaging 2016: Biomedical Applications in Molecular, Structural, and Functional Imaging
Barjor Gimi; Andrzej Krol, Editor(s)

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