Paper
1 April 2016 Frequency-shift low-pass filtering and least mean square adaptive filtering for ultrasound imaging
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Abstract
Ultrasound image quality enhancement is a problem of considerable interest in medical imaging modality and an ongoing challenge to date. This paper investigates a method based on frequency-shift low-pass filtering (FSLF) and least mean square adaptive filtering (LMSAF) for ultrasound image quality enhancement. FSLF is used for processing the ultrasound signal in the frequency domain, while LMSAPF in the time domain. Firstly, FSLF shifts the center frequency of the focused signal to zero. Then the real and imaginary part of the complex data are filtered respectively by finite impulse response (FIR) low-pass filter. Thus the information around the center frequency are retained while the undesired ones, especially background noises are filtered. Secondly, LMSAF multiplies the signals with an automatically adjusted weight vector to further eliminate the noises and artifacts. Through the combination of the two filters, the ultrasound image is expected to have less noises and artifacts and higher resolution, and contrast. The proposed method was verified with the RF data of the CIRS phantom 055A captured by SonixTouch DAQ system. Experimental results show that the background noises and artifacts can be efficiently restrained, the wire object has a higher resolution and the contrast ratio (CR) can be enhanced for about 12dB to 15dB at different image depth comparing to delay-and-sum (DAS).
© (2016) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Shanshan Wang, Chunyu Li, Mingyue Ding, and Ming Yuchi "Frequency-shift low-pass filtering and least mean square adaptive filtering for ultrasound imaging", Proc. SPIE 9790, Medical Imaging 2016: Ultrasonic Imaging and Tomography, 97900P (1 April 2016); https://doi.org/10.1117/12.2216066
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CITATIONS
Cited by 2 scholarly publications.
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KEYWORDS
Image filtering

Linear filtering

Ultrasonography

Digital filtering

Image enhancement

Image quality

Image resolution

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