Automatic detection of subretinal fluid and sub-retinal pigment epithelium fluid in optical coherence tomography images

Age-related macular degeneration (AMD) is the leading cause of blindness in developed countries. Subretinal fluid (SRF) and sub-retinal pigment epithelium (sub-RPE) fluid are signs of AMD and can be detected in optical coherence tomography images. However, manual detection and segmentation of SRFs a...

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Bibliographic Details
Main Authors: Weiguang Ding, Mei Young, Bourgault, Serge, Sieun Lee, Albiani, David A., Kirker, Andrew W., Forooghian, Farzin, Sarunic, Marinko V., Merkur, Andrew B., Beg, Mirza Faisal
Format: Conference Proceeding
Language:English
Subjects:
Adaptive optics
Biomedical optical imaging
Coherence
Image segmentation
Optical imaging
Retina
Tomography
Online Access:Request full text
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Summary:Age-related macular degeneration (AMD) is the leading cause of blindness in developed countries. Subretinal fluid (SRF) and sub-retinal pigment epithelium (sub-RPE) fluid are signs of AMD and can be detected in optical coherence tomography images. However, manual detection and segmentation of SRFs and sub-RPE fluids are laborious and time consuming. In this paper, a novel pipeline is proposed for automatic detection of SRFs and sub-RPE fluids. First, top and bottom layers of retina are segmented using a graph cut method. Then, a Split Bregman-based segmentation method is used to segment dark regions between layers. These segmented regions are considered as potential fluid candidates, on which a set of features are generated. After that, a random forest classifier is trained to distinguish between the true fluid regions from the falsely detected fluid regions. This method shows reasonable performance in a leave-one-out evaluation using a dataset from 21 patients.
ISSN:1094-687X
1558-4615
2694-0604
DOI:10.1109/EMBC.2013.6611265