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In optical coherence tomography (OCT) and ultrasound, unbiased Doppler frequency estimators with low variance are desirable for blood velocity estimation. Hardware improvements in OCT mean that ever higher acquisition rates are possible, which should also, in principle, improve estimation performance. Paradoxically, however, the widely used Kasai(More)
A quantitative signal amplitude estimator for optical coherence tomography (OCT) is presented. It is based on a statistical model of OCT signal and noise, using a Bayesian maximum a posteriori (MAP) estimation framework. Multiple OCT images are used for estimation, similar to the widely utilized intensity averaging method. The estimator is less biased(More)
Recent hardware advances in optical coherence tomography (OCT) have led to ever higher A-scan rates. However, the estimation of blood flow axial velocities is limited by the presence and type of noise. Higher acquisition rates alone do not necessarily enable precise quantification of Doppler velocities, particularly if the estimator is suboptimal. In(More)
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