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Proceedings Paper

Bioelasticity imaging:II. Spatial resolution
Author(s): Larry T. Cook; Yanning Zhu; Timothy J. Hall; Michael F. Insana
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Paper Abstract

The large elasticity contrast possible with strain imaging promises new diagnostic information to augment x-ray, MRI, and ultrasound for the detection of tumors in soft tissue. In the past, we described the design of an elastographic system using the Fourier crosstalk concept introduced by Barrett and Gifford. The diagonal of the crosstalk matrix is related to the pre-sampled modulation transfer function (MTF) of the strain image. Another approach to measuring the spatial resolution of an elasticity image employs a linear frequency- modulated (chirp) strain pattern imposed upon a simulated ultrasonic echo field to study the strain modulation over a range of spatial frequencies in the image. In experiments, high contrast inclusions positioned at varying separations were imaged to apply the Rayleigh criterion for resolution measurement. We measured MTF curves that fell to 0.2 at a spatial frequency of 0.5 mm-1 to 1 mm-1 under realistic conditions. The spatial resolution for ultrasonic strain imaging strongly depends on the transducer properties and deformation patterns applied to the object. Experiments with tissue-like phantoms mimicking the properties of early breast cancer show that 2 mm spheres three times stiffer than the background can be readily resolved. Thus, the potential for using elasticity imaging to detect early breast cancers is excellent.

Paper Details

Date Published: 12 April 2000
PDF: 10 pages
Proc. SPIE 3982, Medical Imaging 2000: Ultrasonic Imaging and Signal Processing, (12 April 2000); doi: 10.1117/12.382240
Show Author Affiliations
Larry T. Cook, Univ. of Kansas Medical Ctr. (United States)
Yanning Zhu, Univ. of Kansas Medical Ctr. (United States)
Timothy J. Hall, Univ. of Kansas Medical Ctr. (United States)
Michael F. Insana, Univ. of California/Davis (United States)


Published in SPIE Proceedings Vol. 3982:
Medical Imaging 2000: Ultrasonic Imaging and Signal Processing
K. Kirk Shung; Michael F. Insana, Editor(s)

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