Tetris: Using Software/Hardware Co-Design to Enable Handheld, Physics-Limited 3D Plane-Wave Ultrasound Imaging

Brendan L. West, Jian Zhou, Ronald G. Dreslinksi, Oliver D. Kripfgans, J. Brian Fowlkes, Chaitali Chakrabarti, Thomas F. Wenisch

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

High volume acquisition rates are imperative for certain medical ultrasound imaging applications, such as 3D elastography and 3D vector flow imaging. As ultrasound imaging transitions from 2D to 3D, the massive data bandwidth and billions of trigonometric operations required to reconstruct each volume leaves conventional computer architectures falling short. Despite recent algorithmic improvements, high-volume-rate ultrasound imaging remains computationally infeasible on known platforms. In this article, we expand our previous work on Tetris, a novel hardware accelerator for separable ultrasound beamforming that enables volume acquisition rates up to the physics limits of acoustic propagation delay. Through algorithmic and hardware optimizations, we enable an image reconstruction system design outclassing previously proposed accelerators in performance while lowering hardware complexity, storage, and power requirements. Tetris operates in a streaming fashion - without requiring on-chip storage of the entire receive signal - reconstructing volumes in real-time. For a representative imaging task, our proposed system generates physics-limited 13,000 volumes per second in a 2 watt power budget. The Tetris beamformer has an unprecedented power efficiency of 2.03 tera-beamforming operations per watt - an increase in efficiency of nearly 3× compared to the prior work.

Original languageEnglish (US)
Article number9076801
Pages (from-to)1209-1220
Number of pages12
JournalIEEE Transactions on Computers
Volume69
Issue number8
DOIs
StatePublished - Aug 1 2020

Keywords

  • Medical imaging
  • accelerator
  • beamforming
  • plane-wave
  • ultrasound

ASJC Scopus subject areas

  • Software
  • Theoretical Computer Science
  • Hardware and Architecture
  • Computational Theory and Mathematics

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