Fully Automated Segmentation of Fluid/Cyst Regions in Optical Coherence Tomography Images With Diabetic Macular Edema Using Neutrosophic Sets and Graph Algorithms

This paper presents a fully automated algorithm to segment fluid-associated (fluid-filled) and cyst regions in optical coherence tomography (OCT) retina images of subjects with diabetic macular edema. The OCT image is segmented using a novel neutrosophic transformation and a graph-based shortest pat...

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Veröffentlicht in:	IEEE transactions on biomedical engineering Jg. 65; H. 5; S. 989 - 1001
Hauptverfasser:	Rashno, Abdolreza, Koozekanani, Dara D., Drayna, Paul M., Nazari, Behzad, Sadri, Saeed, Rabbani, Hossein, Parhi, Keshab K.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	United States IEEE 01.05.2018 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Algorithms Automation Cost function Cysts Cysts - diagnostic imaging Datasets Diabetes Diabetes mellitus Diabetic macular edema Diabetic Retinopathy - diagnostic imaging Edema Epithelium fluid/cyst segmentation graph theory Humans Image Interpretation, Computer-Assisted - methods Image processing Image segmentation Macular Edema - diagnostic imaging neutrosophic set Optical Coherence Tomography Retina Retina - diagnostic imaging Retinal pigment epithelium Sensitivity Sensitivity and Specificity Shortest-path problems Signal processing algorithms Three-dimensional displays Tomography Tomography, Optical Coherence - methods Two dimensional displays
ISSN:	0018-9294, 1558-2531, 1558-2531
Online-Zugang:	Volltext
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