Estimating the ultrasound attenuation coefficient using convolutional neural networks - a feasibility study

@article{Jarosik2022EstimatingTU,
  title={Estimating the ultrasound attenuation coefficient using convolutional neural networks - a feasibility study},
  author={Piotr Jarosik and Michal Byra and Marcin Lewandowski and Ziemowit Klimonda},
  journal={ArXiv},
  year={2022},
  volume={abs/2205.09533}
}
Attenuation coefficient (AC) is a fundamental measure of tissue acoustical properties, which can be used in medical diag-nostics. In this work, we investigate the feasibility of using convolutional neural networks (CNNs) to directly estimate AC from radio-frequency (RF) ultrasound signals. To develop the CNNs we used RF signals collected from tissue mimicking numerical phantoms for the AC values in a range from 0.1 to 1.5 dB/(MHz*cm). The models were trained based on 1-D patches of RF data. We… 

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