We use a random process model for the photocurrent in time-domain optical coherence tomography (TD-OCT) to obtain a maximum likelihood estimate of the reflectance at different depths of an object. This statistical image restoration approach is generally more effective than the previously reported deterministic methods, as it accounts for the statistics of the noise. We also present an expression for the Fisher information matrix in TD-OCT, which could be used to optimize TD-OCT setups. We present theoretical results which we apply to a simulated TD-OCT imaging example.
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