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Quality Digest

FDA Compliance

Tool for Clearer Ultrasound Images

Published: Tuesday, July 24, 2007 - 22:00

(University of Virginia: Charlottesville, Virginia) -- University of Virginia Engineering School Associate Professor William F. Walker and Research Associate Francesco Viola have developed a new tool—an advanced imaging algorithm—that is transforming the way we see things.

Together with graduate student Michael A. Ellis, the biomedical engineering team has created an innovative method of signal processing that can be used with a broad range of imaging and sensing systems, including ultrasound, RADAR, SONAR, telecommunications, and even a few optical imaging systems.

Called the Time-domain Optimized Near-field Estimator (TONE), the algorithm enhances the effectiveness of medical ultrasound imaging, providing medical professionals with dramatically improved image resolution and contrast.

In an ultrasound scanner, computer algorithms use reflected sound waves to create real-time images of the organ or tissue being examined. The images, however, aren’t always clear.

“For almost four decades, beam-forming algorithms have been refined for RADAR and SONAR,” Walker says. “While these algorithms are tremendously powerful, they don’t generally translate well to medical ultrasound imaging.”

When screening for breast cancer or diagnosing other life threatening conditions using ultrasound technology, it’s imperative that images are well-defined. Even so, clinical imaging specialists know that many patients simply “image poorly,” that is, images of their organs and tissues remain unclear.

“Off-axis signals—reflections coming from undesired locations—degrade images produced by current ultrasound systems,” says Viola. “TONE reduces the contribution of these unwanted signals, thereby forming images with greatly increased contrast and resolution”

The team performed a series of simulations using sample ultrasound data to test the performance of this algorithm and compared it to conventional beam-forming strategies (CBF) used by current ultrasound scanners. Imaging trials were conducted using wires suspended in water, a typical set up to test image resolution and contrast in medical ultrasound. The results show a significant improvement in spatial resolution over CBF.

The experiments were performed with technical support from Philips Medical Systems, a long-time collaborator of the University of Virginia team.

The research team also enlisted the support of Interactive SuperComputing—and the company’s product, Star-P, an interactive parallel computing platform—to tackle the computational complexity of the experiments.

According to Walker, the next step will involve using the TONE algorithm to image actual human tissue—the very place where this methodology could have the greatest impact.

“The potential applications for this algorithm are almost infinite,” says James H. Aylor, dean of University of Virginia’s School of Engineering and Applied Science. “Not only can it be used in the medical community to benefit patients nationwide, but it will also have applications in the fields of radio astronomy, seismology and more.”

The research—funded by a grant from the U.S. Army Congressionally Directed Medical Research Program in Breast Cancer—is currently awaiting a patent and will be published in a forthcoming issue of IEEE Transactions on Medical Imaging.

For more information, visit www.virginia.edu/uvatoday/newsRelease.php?id=2352#

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