Implementation and optimization of ultrasound signal processing algorithms on mobile GPU

Woo Kyu Kong; Wooyoul Lee; Kyu Cheol Kim; Yangmo Yoo; Tai-Kyong Song

doi:10.1117/12.2043462

20 March 2014 Implementation and optimization of ultrasound signal processing algorithms on mobile GPU

Woo Kyu Kong, Wooyoul Lee, Kyu Cheol Kim, Yangmo Yoo, Tai-Kyong Song

Proceedings Volume 9040, Medical Imaging 2014: Ultrasonic Imaging and Tomography; 90401F (2014) https://doi.org/10.1117/12.2043462
Event: SPIE Medical Imaging, 2014, San Diego, California, United States

Abstract

A general-purpose graphics processing unit (GPGPU) has been used for improving computing power in medical ultrasound imaging systems. Recently, a mobile GPU becomes powerful to deal with 3D games and videos at high frame rates on Full HD or HD resolution displays. This paper proposes the method to implement ultrasound signal processing on a mobile GPU available in the high-end smartphone (Galaxy S4, Samsung Electronics, Seoul, Korea) with programmable shaders on the OpenGL ES 2.0 platform. To maximize the performance of the mobile GPU, the optimization of shader design and load sharing between vertex and fragment shader was performed. The beamformed data were captured from a tissue mimicking phantom (Model 539 Multipurpose Phantom, ATS Laboratories, Inc., Bridgeport, CT, USA) by using a commercial ultrasound imaging system equipped with a research package (Ultrasonix Touch, Ultrasonix, Richmond, BC, Canada). The real-time performance is evaluated by frame rates while varying the range of signal processing blocks. The implementation method of ultrasound signal processing on OpenGL ES 2.0 was verified by analyzing PSNR with MATLAB gold standard that has the same signal path. CNR was also analyzed to verify the method. From the evaluations, the proposed mobile GPU-based processing method has no significant difference with the processing using MATLAB (i.e., PSNR<52.51 dB). The comparable results of CNR were obtained from both processing methods (i.e., 11.31). From the mobile GPU implementation, the frame rates of 57.6 Hz were achieved. The total execution time was 17.4 ms that was faster than the acquisition time (i.e., 34.4 ms). These results indicate that the mobile GPU-based processing method can support real-time ultrasound B-mode processing on the smartphone.

Citation Download Citation

Woo Kyu Kong, Wooyoul Lee, Kyu Cheol Kim, Yangmo Yoo, and Tai-Kyong Song "Implementation and optimization of ultrasound signal processing algorithms on mobile GPU", Proc. SPIE 9040, Medical Imaging 2014: Ultrasonic Imaging and Tomography, 90401F (20 March 2014); https://doi.org/10.1117/12.2043462

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