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17 February 2020 Improved real-time delay-multiply-and-sum beamforming with coherence factor
Seungwan Jeon, Eun-Yeong Park, Wonseok Choi, Ravi Managuli, Ki Jong Lee, Chulhong Kim
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Proceedings Volume 11240, Photons Plus Ultrasound: Imaging and Sensing 2020; 112403Z (2020) https://doi.org/10.1117/12.2543646
Event: SPIE BiOS, 2020, San Francisco, California, United States
Abstract
Delay-and-sum (DAS) beamforming is the most commonly used algorithm to form photoacoustic (PA) and ultrasound (US) images because of its simple implementation. However, it has several drawbacks such as low image resolution and contrast. To deal with this problem, delay-multiply-and-sum (DMAS) beamforming algorithm was developed a few years ago. It is known that DMAS can improve the image quality by providing higher contrast and narrower main lobe compared to DAS, but its calculation speed is too slow to be implemented for clinical applications. Herein, we introduce an improved DMAS in terms of both imaging speed and quality, and we demonstrated real-time clinical PA imaging. The proposed DMAS provided better lateral resolution and signal-to-noise ratio (SNR) than the original DMAS through a modified coherence factor. Then we accelerated its computation speed by optimizing the algorithm and parallelizing the process using a graphics processing unit (GPU). We quantitatively compared the processing time and the image quality of the proposed algorithm with the conventional algorithms. As the result, it was observed that our proposed algorithm showed better spatial resolution and SNR while achieving real-time imaging framerate. Due to the improvement, the proposed algorithm was successfully implemented on a programmable clinical PA/US imaging system and showed clearer real-time PA images than the conventional DAS images.
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Seungwan Jeon, Eun-Yeong Park, Wonseok Choi, Ravi Managuli, Ki Jong Lee, and Chulhong Kim "Improved real-time delay-multiply-and-sum beamforming with coherence factor", Proc. SPIE 11240, Photons Plus Ultrasound: Imaging and Sensing 2020, 112403Z (17 February 2020); https://doi.org/10.1117/12.2543646
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KEYWORDS
Image processing
Imaging systems
Reconstruction algorithms
Signal to noise ratio
Image quality
Real time imaging
Signal processing
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