Optimal doppler frequency estimators for ultrasound and optical coherence tomography

Aaron C. Chan; Edmund Y. Lam; Vivek Srinivasan

doi:10.1109/BioCAS.2012.6418446

Optimal doppler frequency estimators for ultrasound and optical coherence tomography

Aaron C. Chan, Edmund Y. Lam, Vivek Srinivasan

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

3 Scopus citations

Abstract

The Kasai autocorrelation estimator is widely used in Doppler optical coherence tomography and ultrasound to determine blood velocities. However, as a non-parametric estimator, it may not be optimal. Assuming an additive white Gaussian noise (AWGN) model, we show that the Kasai estimator variance is far from the Cramer-Rao lower bound. Moreover, paradoxically, the Kasai estimator performance degrades as the acquisition rate is increased. By contrast, the additive white Gaussian noise maximum likelihood estimator (AWGN MLE) variance asymptotically approaches the Cramer-Rao lower bound, making it a better estimator at high acquisition rates. Nevertheless, the Kasai estimator outperforms the AWGN MLE under moderate levels of multiplicative decorrelation noise, and could therefore be considered more robust. These findings motivate further work in maximum likelihood estimators under conditions of both additive and multiplicative noise.

Original language	English (US)
Title of host publication	2012 IEEE Biomedical Circuits and Systems Conference
Subtitle of host publication	Intelligent Biomedical Electronics and Systems for Better Life and Better Environment, BioCAS 2012 - Conference Publications
Pages	264-267
Number of pages	4
DOIs	https://doi.org/10.1109/BioCAS.2012.6418446
State	Published - Dec 1 2012
Externally published	Yes
Event	2012 IEEE Biomedical Circuits and Systems Conference: Intelligent Biomedical Electronics and Systems for Better Life and Better Environment, BioCAS 2012 - Hsinchu, Taiwan, Province of China Duration: Nov 28 2012 → Nov 30 2012

Other

Other	2012 IEEE Biomedical Circuits and Systems Conference: Intelligent Biomedical Electronics and Systems for Better Life and Better Environment, BioCAS 2012
Country	Taiwan, Province of China
City	Hsinchu
Period	11/28/12 → 11/30/12

Keywords

Cramer-Rao bounds
Doppler optical coherence tomography
Doppler ultrasound
frequency estimation
maximum likelihood estimation

ASJC Scopus subject areas

Hardware and Architecture
Biomedical Engineering

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Chan, A. C., Lam, E. Y., & Srinivasan, V. (2012). Optimal doppler frequency estimators for ultrasound and optical coherence tomography. In 2012 IEEE Biomedical Circuits and Systems Conference: Intelligent Biomedical Electronics and Systems for Better Life and Better Environment, BioCAS 2012 - Conference Publications (pp. 264-267). [6418446] https://doi.org/10.1109/BioCAS.2012.6418446

Optimal doppler frequency estimators for ultrasound and optical coherence tomography. / Chan, Aaron C.; Lam, Edmund Y.; Srinivasan, Vivek.

2012 IEEE Biomedical Circuits and Systems Conference: Intelligent Biomedical Electronics and Systems for Better Life and Better Environment, BioCAS 2012 - Conference Publications. 2012. p. 264-267 6418446.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Chan, AC, Lam, EY & Srinivasan, V 2012, Optimal doppler frequency estimators for ultrasound and optical coherence tomography. in 2012 IEEE Biomedical Circuits and Systems Conference: Intelligent Biomedical Electronics and Systems for Better Life and Better Environment, BioCAS 2012 - Conference Publications., 6418446, pp. 264-267, 2012 IEEE Biomedical Circuits and Systems Conference: Intelligent Biomedical Electronics and Systems for Better Life and Better Environment, BioCAS 2012, Hsinchu, Taiwan, Province of China, 11/28/12. https://doi.org/10.1109/BioCAS.2012.6418446

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abstract = "The Kasai autocorrelation estimator is widely used in Doppler optical coherence tomography and ultrasound to determine blood velocities. However, as a non-parametric estimator, it may not be optimal. Assuming an additive white Gaussian noise (AWGN) model, we show that the Kasai estimator variance is far from the Cramer-Rao lower bound. Moreover, paradoxically, the Kasai estimator performance degrades as the acquisition rate is increased. By contrast, the additive white Gaussian noise maximum likelihood estimator (AWGN MLE) variance asymptotically approaches the Cramer-Rao lower bound, making it a better estimator at high acquisition rates. Nevertheless, the Kasai estimator outperforms the AWGN MLE under moderate levels of multiplicative decorrelation noise, and could therefore be considered more robust. These findings motivate further work in maximum likelihood estimators under conditions of both additive and multiplicative noise.",

keywords = "Cramer-Rao bounds, Doppler optical coherence tomography, Doppler ultrasound, frequency estimation, maximum likelihood estimation",

author = "Chan, {Aaron C.} and Lam, {Edmund Y.} and Vivek Srinivasan",

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N2 - The Kasai autocorrelation estimator is widely used in Doppler optical coherence tomography and ultrasound to determine blood velocities. However, as a non-parametric estimator, it may not be optimal. Assuming an additive white Gaussian noise (AWGN) model, we show that the Kasai estimator variance is far from the Cramer-Rao lower bound. Moreover, paradoxically, the Kasai estimator performance degrades as the acquisition rate is increased. By contrast, the additive white Gaussian noise maximum likelihood estimator (AWGN MLE) variance asymptotically approaches the Cramer-Rao lower bound, making it a better estimator at high acquisition rates. Nevertheless, the Kasai estimator outperforms the AWGN MLE under moderate levels of multiplicative decorrelation noise, and could therefore be considered more robust. These findings motivate further work in maximum likelihood estimators under conditions of both additive and multiplicative noise.

AB - The Kasai autocorrelation estimator is widely used in Doppler optical coherence tomography and ultrasound to determine blood velocities. However, as a non-parametric estimator, it may not be optimal. Assuming an additive white Gaussian noise (AWGN) model, we show that the Kasai estimator variance is far from the Cramer-Rao lower bound. Moreover, paradoxically, the Kasai estimator performance degrades as the acquisition rate is increased. By contrast, the additive white Gaussian noise maximum likelihood estimator (AWGN MLE) variance asymptotically approaches the Cramer-Rao lower bound, making it a better estimator at high acquisition rates. Nevertheless, the Kasai estimator outperforms the AWGN MLE under moderate levels of multiplicative decorrelation noise, and could therefore be considered more robust. These findings motivate further work in maximum likelihood estimators under conditions of both additive and multiplicative noise.

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Optimal doppler frequency estimators for ultrasound and optical coherence tomography

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Keywords

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