Ms. Emelina P. Vienneau Profile

Emelina P. Vienneau

at Vanderbilt Univ

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Publications (2)

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Proceedings Article | 1 April 2024 Presentation + Paper

Using domain adaptive deep neural networks to improve transthoracic echocardiography

Lening Cui, Christopher Khan, Ying-Chun Pan, Siegfried Schlunk, Emelina Vienneau, Emmanuel Ofosu, Jason Harbert, Ryan LeFevre, Susan Eagle, Brett Byram

Proceedings Volume 12932, 129320M (2024) https://doi.org/10.1117/12.3008175

KEYWORDS: In vivo imaging, Phased arrays, Echocardiography, Neural networks, Image quality

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We previously showed that domain adaptive deep neural networks (DNNs) can outperform delay-and-sum (DAS) beamforming in the context of abdominal imaging. We hypothesize the ability of our domain adaptive DNN framework to be applied to transthoracic echocardiography (TTE). We also propose architectural improvements, such as leveraging an encoder-decoder structure and skip connections, to further improve ultrasound image quality for echocardiography tasks such as the detection of thrombi in the left atrial appendage (LAA). DNN training data utilized simulated and in vivo cardiac data. Simulated anechoic and hypoechoic cysts with various amounts of clutter were generated through Field II and in vivo data was collected by scanning patients at Vanderbilt University Medical Center. Fundamental frequency TTE data from five separate cases were processed with DAS, ADMIRE, the baseline model, and multiple models with modified architectures. We found that even when varying the amount of training data, the DNNs consistently achieved higher generalized contrast-to-noise (gCNR) and contrast ratio (CR) but lower contrast-to-noise ratio when compared to DAS. The best-performing beamformer was one DNN with our architectural improvements, achieving higher average gCNR and CR values of .907 and 48.30 dB compared to the baseline DNN values of .788 and 39.45dB, and DAS values of .717 and 14.08dB. Our results demonstrate that our domain adaptive DNN can effectively be applied in the context of transthoracic cardiology, and an encoder-decoder architecture with skip connections can result in even more improvements. Further advancements may improve image quality even more.

Proceedings Article | 15 February 2021 Presentation + Paper

A coded excitation framework for increased signal-to-noise ratio of in vivo ultrasound power Doppler imaging

Emelina Vienneau, Brett Byram

Proceedings Volume 11602, 116020P (2021) https://doi.org/10.1117/12.2582344

KEYWORDS: Signal to noise ratio, In vivo imaging, Ultrasonography, Doppler effect, Blood circulation, Skull, Signal processing, Signal attenuation, Scanners, Safety

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Ultrasound power Doppler imaging is a useful clinical tool for measuring perfusion. Sensitivity to slow moving blood flow is important for many clinical applications, but thick abdominal walls or the presence of bone such as ribs or the skull cause significant attenuation and thereby reduce the signal-to-noise ratio (SNR) and flow sensitivity. One way to improve SNR is to inject microbubble contrast agents into the vascular system, but this is impractical for many applications. An alternative approach is to use coded excitation, a signal processing technique that can drastically increase SNR within FDA safety limits without contrast agents. This work encompasses a method to design long coded pulses that are simple to implement along with a pulse compression technique to completely suppress range lobes, thereby recovering axial resolution, maintaining contrast, and improving SNR by as much as a factor of 10log10(code length). In simulations we show that this approach reliably improves the SNR of power Doppler imaging across a range of noise levels. As the noise level increases with respect to the blood, contrast and contrast-to-noise ratio are maintained with coded excitation whereas they drop precipitously without coded excitation. In vivo feasibility is also shown in transcranial and transthoracic cardiac B-Mode imaging. Both simulation and in vivo results match theoretical expectations of SNR gain. Finally, preliminary results showing in vivo power Doppler imaging in the liver are presented as well. Coded excitation is able to improve the blood vessel to background CNR and CR as compared to a standard approach.

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