Modeling of Retinal Optical Coherence Tomography Based on Stochastic Differential Equations: Application to Denoising

In this paper a statistical modeling, based on stochastic differential equations (SDEs), is proposed for retinal Optical Coherence Tomography (OCT) images. In this method, pixel intensities of image are considered as discrete realizations of a Levy stable process. This process has independent increm...

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Veröffentlicht in:	IEEE transactions on medical imaging Jg. 40; H. 8; S. 2129 - 2141
Hauptverfasser:	Tajmirriahi, Mahnoosh, Amini, Zahra, Hamidi, Arsham, Zam, Azhar, Rabbani, Hossein
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	United States IEEE 01.08.2021 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Algorithms Alternating direction method of multipliers~(ADMM) algorithm Differential equations Formulas (mathematics) Fractals fractional Laplacian Goodness of fit Histograms Image classification Image segmentation Laplace equations Laplace transforms Mathematical model Mathematical models Noise Noise reduction Operators (mathematics) Optical Coherence Tomography optical coherence tomography~(OCT) image Optimization Pixels Regularization Retina Statistical analysis Statistical models Statistical tests stochastic differential equation (SDE) Stochastic processes Stochasticity Technological innovation Tomography
ISSN:	0278-0062, 1558-254X, 1558-254X
Online-Zugang:	Volltext
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