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1 results

  • 10 - Deep Learning for Ultrasound Beamforming

  • from Part II - Deep-Learning Architecture for Various Imaging Architectures
  • Edited by Jong Chul Ye, Korea Advanced Institute of Science and Technology (KAIST), Yonina C. Eldar, Weizmann Institute of Science, Israel, Michael Unser, École Polytechnique Fédérale de Lausanne
  • Book:
    Deep Learning for Biomedical Image Reconstruction
    Published online:
    15 September 2023
    Print publication:
    12 October 2023, pp 223-251

  • Summary

    With the present demand for high-quality image reconstruction and signal extraction from less (e.g., unfocused or parallel) transmissions that facilitate fast imaging, and the push towards compact probes, modern ultrasound imaging leans heavily on innovations in powerful digital receive channel processing. Beamforming, the process of mapping received ultrasound echoes to the spatial image domain, naturally lies at the heart of the ultrasound image formation chain. In this chapter, we discuss why and when deep learning methods can play a compelling role in the digital beamforming pipeline, and then show how these data-driven systems can be leveraged for improved ultrasound image reconstruction.