Speckle statistics in OCT images: Monte Carlo simulations and experimental studies

The speckle pattern of an optical coherence tomography (OCT) image carries potentially useful sample information that may assist in tissue characterization. Recent biomedical results in vivo indicate that the distribution of signal intensities within an OCT tissue image is well described by a log-no...

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Bibliographic Details
Published in:Optics letters 2014-06, Vol.39 (12), p.3472-3475
Main Authors: Kirillin, Mikhail Yu, Farhat, Golnaz, Sergeeva, Ekaterina A, Kolios, Michael C, Vitkin, Alex
Format: Article
Language:English
Subjects:
Computer Simulation
Diagnostic systems
Humans
Mathematical models
Microspheres
Monte Carlo Method
Monte Carlo methods
Optical Phenomena
Phantoms, Imaging
Samples
Statistical methods
Statistics
Tomography, Optical Coherence - methods
Tomography, Optical Coherence - statistics & numerical data
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Summary:The speckle pattern of an optical coherence tomography (OCT) image carries potentially useful sample information that may assist in tissue characterization. Recent biomedical results in vivo indicate that the distribution of signal intensities within an OCT tissue image is well described by a log-normal-like (Gamma) function. To fully understand and exploit this finding, an OCT Monte Carlo model that accounts for speckle effects was developed. The resultant Monte Carlo speckle statistics predictions agree well with experimental OCT results from a series of control phantoms with variable scattering properties; the Gamma distribution provides a good fit to the theoretical and experimental results. The ability to quantify subresolution tissue features via OCT speckle analysis may prove useful in diagnostic photomedicine.
ISSN:0146-9592
1539-4794
DOI:10.1364/OL.39.003472