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A GPU framework for ultrasound color flow imaging (CFI) based on auto-correlation is presented. The parallel CFI processing framework implementation is mainly based on CUDA performance features, such as the memory selection strategy, applicable thread structure and high-throughput bandwidth. Parallel convolution algorithm and multi-channel championship algorithm are proposed. This CFI method achieves...
The Compute Unified Device Architecture (CUDA) is a new programming platform making use of the unified shader design of the most current Graphics Processing Units (GPUs) from NVIDIA. In this paper, we apply this revolutionary new technology to implement the automatic time gain compensation (ATGC) for medical ultrasound imaging. The parallel box filtering method and general matrix computation algorithms...
A GPU framework for ultrasound speckle reduction by region growing based on local statistics extracted from the histogram shape is presented. The required image processing is computationally intensive, involving histogram calculation, region growing, box filtering using different sizes of windows, and more. In this paper, we describe the use of a graphics processing unit for implementing image processing...
Pulsed Wave (PW) spectrum Doppler ultrasound is a valuable tool for clinical diagnosis for flow velocity distribution in vessels. However, real-time processing of PW spectrum is computationally intensive, involving wall filtering, Fast Fourier Transform (FFT), column filtering and linear averaging. In this paper a very efficient implementation of a PW Doppler spectrum ultrasound using the Compute...
Ultrasound B-mode imaging is the basic image mode which can offer anatomic information of organs for clinical diagnosis. Because of the massive computation involved in baseband processing from focused radio-frequency (RF) signals followed by envelop detection, compression and scan conversion required for high quality B-mode imaging, existing medical systems always rely on complicated hardware in real...
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