Research interface on a programmable ultrasound scanner
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Updated: Jul 7, 2026

An Experimental Protocol for Assessing the Performance of New Ultrasound Probes Based on CMUT Technology in Application to Brain Imaging
Published on: September 24, 2017
Vijay Shamdasani1, Unmin Bae, Siddhartha Sikdar
1Department of Bioengineering, University of Washington, Seattle, WA 98195-5061, USA.
Motivation:
Commercial ultrasound machines in the past did not provide the ultrasound researchers access to raw ultrasound data. Lack of this ability has impeded evaluation and clinical testing of novel ultrasound algorithms and applications.
Objectives:
Recently, we developed a flexible ultrasound back-end where all the processing for the conventional ultrasound modes, such as B, M, color flow and spectral Doppler, was performed in software. The back-end has been incorporated into a commercial ultrasound machine, the Hitachi HiVision 5500. The goal of this work is to develop an ultrasound research interface on the back-end for acquiring raw ultrasound data from the machine.
Methods:
The research interface has been designed as a software module on the ultrasound back-end. To increase the amount of raw ultrasound data that can be spooled in the limited memory available on the back-end, we have developed a method that can losslessly compress the ultrasound data in real time.
Results And Discussion:
The raw ultrasound data could be obtained in any conventional ultrasound mode, including duplex and triplex modes. Furthermore, use of the research interface does not decrease the frame rate or otherwise affect the clinical usability of the machine. The lossless compression of the ultrasound data in real time can increase the amount of data spooled by approximately 2.3 times, thus allowing more than 6s of raw ultrasound data to be acquired in all the modes. The interface has been used not only for early testing of new ideas with in vitro data from phantoms, but also for acquiring in vivo data for fine-tuning ultrasound applications and conducting clinical studies. We present several examples of how newer ultrasound applications, such as elastography, vibration imaging and 3D imaging, have benefited from this research interface. Since the research interface is entirely implemented in software, it can be deployed on existing HiVision 5500 ultrasound machines and may be easily upgraded in the future.
Conclusions:
The developed research interface can aid researchers in the rapid testing and clinical evaluation of new ultrasound algorithms and applications. Additionally, we believe that our approach would be applicable to designing research interfaces on other ultrasound machines.
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