Automated segmentation of intraretinal cystoid macular edema based on Gaussian mixture model

Automated segmentation of intraretinal cystoid macular edema based on Gaussian mixture model

We introduce a method based on Gaussian mixture model (GMM) clustering and level-set to automatically detect intraretina fluid on diabetic retinopathy (DR) from spectral domain optical coherence tomography (SD-OCT) images in this paper. First, each B-scan is segmented using GMM clustering. The origi...

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Bibliographic Details
Main Authors: Jinghong Wu, Sijie Niu, Qiang Chen, Wen Fan, Songtao Yuan, Dengwang Li
Format: Article
Language:English
Published: World Scientific Publishing 2020-01-01
Series:Journal of Innovative Optical Health Sciences
Subjects:
gaussian mixture model
level-set
spectral domain optical coherence tomography (sd-oct)
segmentation
Online Access:http://www.worldscientific.com/doi/pdf/10.1142/S1793545819500202
Description
Summary:We introduce a method based on Gaussian mixture model (GMM) clustering and level-set to automatically detect intraretina fluid on diabetic retinopathy (DR) from spectral domain optical coherence tomography (SD-OCT) images in this paper. First, each B-scan is segmented using GMM clustering. The original clustering results are refined using location and thickness information. Then, the spatial information among every consecutive five B-scans is used to search potential fluid. Finally, the improved level-set method is used to obtain the accurate boundaries. The high sensitivity and accuracy demonstrated here show its potential for detection of fluid.
ISSN:1793-5458
1793-7205

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