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11 April 2018 Nanoparticle-enabled experimentally trained wavelet-domain denoising method for optical coherence tomography
Irina N. Dolganova, Nikita V. Chernomyrdin, Polina V. Aleksandrova, Sheyh-Islyam T. Beshplav, Aleksandr A. Potapov M.D., Igor V. Reshetov, Vladimir N. Kurlov, Valery V. Tuchin, Kirill I. Zaytsev
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Journal of Biomedical Optics, Vol. 23, Issue 9, 091406 (April 2018). https://doi.org/10.1117/1.JBO.23.9.091406
Abstract
We present the nanoparticle-enabled experimentally trained wavelet-domain denoising method for optical coherence tomography (OCT). It employs an experimental training algorithm based on imaging of a test-object, made of the colloidal suspension of the monodisperse nanoparticles and contains the microscale inclusions. The geometry and the scattering properties of the test-object are known a priori allowing us to set the criteria for the training algorithm. Using a wide set of the wavelet kernels and the wavelet-domain filtration approaches, the appropriate filter is constructed based on the test-object imaging. We apply the proposed approach and chose an efficient wavelet denoising procedure by considering the combinations of the decomposition basis from five wavelet families with eight types of the filtration threshold. We demonstrate applicability of the wavelet-filtering for the in vitro OCT image of human brain meningioma. The observed results prove high efficiency of the proposed OCT image denoising technique.
© 2018 Society of Photo-Optical Instrumentation Engineers (SPIE) 1083-3668/2018/$25.00 © 2018 SPIE
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Irina N. Dolganova, Nikita V. Chernomyrdin, Polina V. Aleksandrova, Sheyh-Islyam T. Beshplav, Aleksandr A. Potapov M.D., Igor V. Reshetov, Vladimir N. Kurlov, Valery V. Tuchin, and Kirill I. Zaytsev "Nanoparticle-enabled experimentally trained wavelet-domain denoising method for optical coherence tomography," Journal of Biomedical Optics 23(9), 091406 (11 April 2018). https://doi.org/10.1117/1.JBO.23.9.091406
Received: 5 January 2018; Accepted: 16 March 2018; Published: 11 April 2018
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Cited by 16 scholarly publications.
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KEYWORDS
Optical coherence tomography
Denoising
Wavelets
Image filtering
Scattering
Tissues
Nanoparticles
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