Differentiable Beamforming for Distributed Attenuation Estimation and Spatial Gain Compensation (SGC)

Ultrasound imaging with automatic differentiation has emerged as a technique to map many model-based approaches for estimating physical beamforming or tissue parameters onto a differentiable computational graph. Using a tomographic model, we adapt this approach to enable highly precise and accurate...

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Bibliographic Details
Main Authors: Frey, Benjamin N., Hyun, Dongwoon, Simson, Walter, Brevett, Thurston, Zhuang, Louise, Baek, Jihye, Sanabria, Sergio J., Dahl, Jeremy J.
Format: Conference Proceeding
Language:English
Subjects:
Adaptation models
Array signal processing
Attenuation
attenuation imaging
Computational modeling
computed tomography
Data models
differentiable beamforming
Estimation
Image reconstruction
Signal to noise ratio
Tomography
Ultrasonic imaging
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Summary:Ultrasound imaging with automatic differentiation has emerged as a technique to map many model-based approaches for estimating physical beamforming or tissue parameters onto a differentiable computational graph. Using a tomographic model, we adapt this approach to enable highly precise and accurate distributed attenuation estimation. We present a novel sub-aperture difference method for attenuation estimation on simulated and experimental ultrasound channel data. The presented attenuation estimation model estimates attenuation with less than 44 mdB/cm/MHz on simulated inclusion data, and 119 mdB/cm/MHz on simulated uniform attenuation data, but is challenged by experimental data with low signal-to-noise ratio and the selection of an a priori estimate of the attenuation.
ISSN:2375-0448
DOI:10.1109/UFFC-JS60046.2024.10794091