Aaron C. Chan

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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)
In optical coherence tomography (OCT), unbiased and low variance Doppler frequency estimators are desirable for blood velocity estimation. Hardware improvements in OCT mean that ever higher acquisition rates are possible. However, it is known that the Kasai autocorrelation estimator, unexpectedly, performs worse as acquisition rates increase. Here we(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)
We propose using maximum a-posteriori (MAP) estimation to improve the image signal-to-noise ratio (SNR) in polarization diversity (PD) optical coherence tomography. PD-detection removes polarization artifacts, which are common when imaging highly birefringent tissue or when using a flexible fiber catheter. However, dividing the probe power to two(More)
We show by a combination of theoretical argument and computer search that if a projective (75, 4, 12, 5) set in PG(3, 7) exists then its automorphism group must be trivial. This corresponds to the smallest open case of a coding problem posed by H. Ward in 1998, concerning the possible existence of an infinite family of projective two-weight codes meeting(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)
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