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Proceedings Paper

Frequency compounding in multifrequency vibroacoustography
Author(s): Matthew W. Urban; Azra Alizad; Mostafa Fatemi
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Paper Abstract

Vibro-acoustography is a speckle-free ultrasound based imaging modality that can visualize normal and abnormal soft tissue through mapping stimulated acoustic emission. The acoustic emission is generated by focusing two ultrasound beams of slightly different frequencies (Δf = f1-f2) to the same spatial location and vibrating the tissue as a result of ultrasound radiation force. Reverberation of the acoustic emission can create dark and bright areas in the image that affect overall image contrast and detectability of abnormal tissue. Using finite length tonebursts yields acoustic emission at Δf and at sidebands centered about Δf that originate from the temporal toneburst gating. Separate images are formed by bandpass filtering the acoustic emission at Δf and the associated sidebands. The data at these multiple frequencies are compounded through coherent or incoherent processes to reduce the artifacts associated with reverberation of the acoustic emission. Experimental results from a urethane breast phantom and in vivo human breast scans are shown. The reduction in reverberation artifacts are analyzed using a smoothness metric which uses the variances of the gray levels of the original images and those formed through coherent and incoherent compounding of image data. This smoothness metric is minimized when the overall image background is smooth while image features are still preserved. The smoothness metric indicates that the images improved by factors from 1.23-4.33 and 1.09-2.68 in phantom and in vivo studies, respectively. The coherent and incoherent compounding of multifrequency data demonstrate, both qualitatively and quantitatively, the efficacy of this method for reduction of reverberation artifacts.

Paper Details

Date Published: 13 March 2009
PDF: 8 pages
Proc. SPIE 7265, Medical Imaging 2009: Ultrasonic Imaging and Signal Processing, 726511 (13 March 2009); doi: 10.1117/12.811770
Show Author Affiliations
Matthew W. Urban, Mayo Clinic College of Medicine (United States)
Azra Alizad, Mayo Clinic College of Medicine (United States)
Mostafa Fatemi, Mayo Clinic College of Medicine (United States)

Published in SPIE Proceedings Vol. 7265:
Medical Imaging 2009: Ultrasonic Imaging and Signal Processing
Stephen A. McAleavey; Jan D'hooge, Editor(s)

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