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, quite literally, transforming the way we see things.
Together with graduate student Michael A. Ellis, 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), this novel 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, beamforming algorithms have been refined for RADAR and SONAR,” said Walker. “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 is 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” said 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 beamforming strategies (CBF) used by current ultrasound scanners. Imaging trials were conducted using wires (see attached illustration) 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 U.Va. 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,” said James H. Aylor, dean of U.Va.'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 patent pending and will be published in a forthcoming issue of IEEE Transactions on Medical Imaging .
About the University of Virginia School of Engineering and Applied Science
Founded in 1836, the University of Virginia School of Engineering and Applied Science combines research and educational opportunities at the undergraduate and graduate levels. Within the undergraduate programs, courses in engineering, ethics, mathematics, the sciences and the humanities are available to build a strong foundation for careers in engineering and other professions. Its abundant research opportunities complement the curriculum and educate young men and women to become thoughtful leaders in technology and society. At the graduate level, the Engineering School collaborates with the University's highly ranked medical and business schools on interdisciplinary research projects and entrepreneurial initiatives. With a distinguished faculty and a student body of 2,200 undergraduates and 700 graduate students, the Engineering School offers an array of engineering disciplines, including cutting-edge research programs in computer and information science and engineering, bioengineering and nanotechnology. For more information, visit