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8 May 2014 A complex noise reduction method for improving visualization of SD-OCT skin biomedical images
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In this paper we consider the original method of solving noise reduction problem for visualization’s quality improvement of SD-OCT skin and tumors biomedical images. The principal advantages of OCT are high resolution and possibility of in vivo analysis. We propose a two-stage algorithm: 1) process of raw one-dimensional A-scans of SD-OCT and 2) remove a noise from the resulting B(C)-scans. The general mathematical methods of SD-OCT are unstable: if the noise of the CCD is 1.6% of the dynamic range then result distortions are already 25-40% of the dynamic range. We use at the first stage a resampling of A-scans and simple linear filters to reduce the amount of data and remove the noise of the CCD camera. The efficiency, improving productivity and conservation of the axial resolution when using this approach are showed. At the second stage we use an effective algorithms based on Hilbert-Huang Transform for more accurately noise peaks removal. The effectiveness of the proposed approach for visualization of malignant and benign skin tumors (melanoma, BCC etc.) and a significant improvement of SNR level for different methods of noise reduction are showed. Also in this study we consider a modification of this method depending of a specific hardware and software features of used OCT setup. The basic version does not require any hardware modifications of existing equipment. The effectiveness of proposed method for 3D visualization of tissues can simplify medical diagnosis in oncology.
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Oleg O. Myakinin, Valery P. Zakharov, Ivan A. Bratchenko, Dmitry V. Kornilin, and Alexander G. Khramov "A complex noise reduction method for improving visualization of SD-OCT skin biomedical images", Proc. SPIE 9129, Biophotonics: Photonic Solutions for Better Health Care IV, 91292Y (8 May 2014);

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