GPU-based real-time small displacement estimation with ultrasound.

Published

Journal Article

General purpose computing on graphics processing units (GPUs) has been previously shown to speed up computationally intensive data processing and image reconstruction algorithms for computed tomography (CT), magnetic resonance (MR), and ultrasound images. Although some algorithms in ultrasound have been converted to GPU processing, many investigative ultrasound research systems still use serial processing on a single CPU. One such ultrasound modality is acoustic radiation force impulse (ARFI) imaging, which investigates the mechanical properties of soft tissue. Traditionally, the raw data are processed offline to estimate the displacement of the tissue after the application of radiation force. It is highly advantageous to process the data in real-time to assess their quality and make modifications during a study. In this paper, we present algorithms for efficient GPU parallel processing of two widely used tools in ultrasound: cubic spline interpolation and Loupas' two-dimensional autocorrelator for displacement estimation. It is shown that a commercially available graphics card can be used for these computations, achieving speed increases up to 40x compared with single CPU processing. Thus, we conclude that the GPU-based data processing approach facilitates real-time (i.e., <1 second) display of ARFI data and is a promising approach for ultrasonic research systems.

Full Text

Duke Authors

Cited Authors

  • Rosenzweig, S; Palmeri, M; Nightingale, K

Published Date

  • February 2011

Published In

Volume / Issue

  • 58 / 2

Start / End Page

  • 399 - 405

PubMed ID

  • 21342825

Pubmed Central ID

  • 21342825

Electronic International Standard Serial Number (EISSN)

  • 1525-8955

International Standard Serial Number (ISSN)

  • 0885-3010

Digital Object Identifier (DOI)

  • 10.1109/TUFFC.2011.1817

Language

  • eng