Abstract

Parametric imaging of the attenuation coefficient using optical coherence tomography (OCT) is a promising approach for evaluating abnormalities in tissue. To date, a standardized measure of accuracy and precision of by the depth-resolved estimation (DRE) method, as an alternative to least squares fitting, is missing. We present a robust theoretical framework to determine accuracy and precision of the DRE of . We derive and validate analytical expressions for the accuracy and precision of determination by the DRE using simulated OCT signals in absence and presence of noise. We compare the theoretically achievable precisions of the DRE method and the least-squares fitting approach. Our analytical expressions agree with the numerical simulations for high signal-to-noise ratios and qualitatively describe the dependence on noise otherwise. A commonly used simplification of the DRE method results in a systematic overestimation of the attenuation coefficient in the order of , where is the pixel stepsize. When , is reconstructed with higher precision by the depth-resolved method compared to fitting over the length of an axial fitting range . We derived and validated expressions for the accuracy and precision of DRE of . A commonly used simplification of this method is not recommended as being used for OCT-attenuation reconstruction. We give a rule of thumb providing guidance in the choice of estimation method.

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