GPU-based real-time small displacement estimation with ultrasound.
Journal Article (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
- PMC3408661
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