University of Virginia Engineering School Associate Professor William F. Walker and Research Associate Francesco Viola have developed an imaging algorithm that promises to literally transform the way we see things.
Together with graduate student Michael Ellis, they have created a new method processing signals that can be used with a 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), their novel adaptive beamforming algorithm enhances the effectiveness of medical ultrasound imaging, providing medical professionals with dramatically improved image resolution and contrast.
For over fifty years, adaptive beamforming (ABF) algorithms have been applied in radar and sonar signal processing. These algorithms reduce the contribution of undesired off-axis signals while maintaining a desired response along a specific direction. Typically, ABF achieves higher resolution and contrast than conventional beamforming (CBF), at the price of an increased computational load. Now, the researchers have brought the same ABF technique to the medical field.
‘Off-axis signals – reflections coming from undesired locations – degrade images produced by current ultrasound systems,’ said Francesco Viola. ‘TONE reduces the contribution of these unwanted signals, thereby images are formed with greatly increased contrast and resolution.’
The team performed a series of simulations using sample ultrasound data to test the performance of the algorithm and compared it to conventional beamforming strategies (CBF) used by current ultrasound scanners. 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 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 the methodology could have the greatest impact.
The technology – funded by a grant from the US Army Congressionally Directed Medical Research Program in Breast Cancer – is currently patent pending.