Mathematical model for separating signal and noise in dynamic optical coherence tomography (dOCT)

Gereon M. Hüttmann

doi:10.1117/12.3005716

13 March 2024 Mathematical model for separating signal and noise in dynamic optical coherence tomography (dOCT)

Gereon M. Hüttmann

Proceedings Volume PC12830, Optical Coherence Tomography and Coherence Domain Optical Methods in Biomedicine XXVIII; PC1283029 (2024) https://doi.org/10.1117/12.3005716
Event: SPIE BiOS, 2024, San Francisco, California, United States

Abstract

Dynamic optical coherence tomography (dOCT) uses signal fluctuation for contrasting different cellular and acellular components in living biological tissue. The autocorrelation or Fourier transform of time series of OCT measurements are converted to a color contrast. However, a quantitative analysis is still challenging. Here we investigate theoretically, how noise of the OCT measurement influences the fluctuation spectra. Probability functions are derived for the different components in the spectra and validated by numerical simulation. With an appropriate calibration of the OCT device a separation of OCT noise and a quantification the dynamic OCT should be feasible.

Conference Presentation

Citation Download Citation

Gereon M. Hüttmann "Mathematical model for separating signal and noise in dynamic optical coherence tomography (dOCT)", Proc. SPIE PC12830, Optical Coherence Tomography and Coherence Domain Optical Methods in Biomedicine XXVIII, PC1283029 (13 March 2024); https://doi.org/10.1117/12.3005716

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