Automated detection of dilated capillaries on optical coherence tomography angiography

Automated detection and grading of angiographic high-risk features in diabetic retinopathy can potentially enhance screening and clinical care. We have previously identified capillary dilation in angiograms of the deep plexus in optical coherence tomography angiography as a feature associated with s...

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Published in:Biomedical optics express 2017-02, Vol.8 (2), p.1101-1109
Main Authors: Dongye, Changlei, Zhang, Miao, Hwang, Thomas S, Wang, Jie, Gao, Simon S, Liu, Liang, Huang, David, Wilson, David J, Jia, Yali
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container_end_page 1109
container_issue 2
container_start_page 1101
container_title Biomedical optics express
container_volume 8
creator Dongye, Changlei
Zhang, Miao
Hwang, Thomas S
Wang, Jie
Gao, Simon S
Liu, Liang
Huang, David
Wilson, David J
Jia, Yali
description Automated detection and grading of angiographic high-risk features in diabetic retinopathy can potentially enhance screening and clinical care. We have previously identified capillary dilation in angiograms of the deep plexus in optical coherence tomography angiography as a feature associated with severe diabetic retinopathy. In this study, we present an automated algorithm that uses hybrid contrast to distinguish angiograms with dilated capillaries from healthy controls and then applies saliency measurement to map the extent of the dilated capillary networks. The proposed algorithm agreed well with human grading.
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title Automated detection of dilated capillaries on optical coherence tomography angiography
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