Wavelet-domain de-noising of OCT images of human brain malignant glioma

I. N. Dolganova; P. V. Aleksandrova; S.-I. T. Beshplav; N. V. Chernomyrdin; E. N. Dubyanskaya; S. A. Goryaynov; V. N. Kurlov; I. V. Reshetov; A. A. Potapov; V. V. Tuchin; K. I. Zaytsev

doi:10.1117/12.2314727

26 April 2018 Wavelet-domain de-noising of OCT images of human brain malignant glioma

I. N. Dolganova, P. V. Aleksandrova, S.-I. T. Beshplav, N. V. Chernomyrdin, E. N. Dubyanskaya, S. A. Goryaynov, V. N. Kurlov, I. V. Reshetov, A. A. Potapov, V. V. Tuchin, K. I. Zaytsev

Author Affiliations +

Proceedings Volume 10717, Saratov Fall Meeting 2017: Laser Physics and Photonics XVIII; and Computational Biophysics and Analysis of Biomedical Data IV; 107171X (2018) https://doi.org/10.1117/12.2314727
Event: Saratov Fall Meeting 2017, 2017, Saratov, Russian Federation

Abstract

We have proposed a wavelet-domain de-noising technique for imaging of human brain malignant glioma by optical coherence tomography (OCT). It implies OCT image decomposition using the direct fast wavelet transform, thresholding of the obtained wavelet spectrum and further inverse fast wavelet transform for image reconstruction. By selecting both wavelet basis and thresholding procedure, we have found an optimal wavelet filter, which application improves differentiation of the considered brain tissue classes – i.e. malignant glioma and normal/intact tissue. Namely, it allows reducing the scattering noise in the OCT images and retaining signal decrement for each tissue class. Therefore, the observed results reveals the wavelet-domain de-noising as a prospective tool for improved characterization of biological tissue using the OCT.

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I. N. Dolganova, P. V. Aleksandrova, S.-I. T. Beshplav, N. V. Chernomyrdin, E. N. Dubyanskaya, S. A. Goryaynov, V. N. Kurlov, I. V. Reshetov, A. A. Potapov, V. V. Tuchin, and K. I. Zaytsev "Wavelet-domain de-noising of OCT images of human brain malignant glioma", Proc. SPIE 10717, Saratov Fall Meeting 2017: Laser Physics and Photonics XVIII; and Computational Biophysics and Analysis of Biomedical Data IV, 107171X (26 April 2018); https://doi.org/10.1117/12.2314727

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