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Optimized GPU Framework for Ultrasound Color Flow Imaging

Zhengjuan Fan, Dan Shi, D.C. Liu
Comput. Sci. Coll., Sichuan Univ., Chengdu, China
4th International Conference on Bioinformatics and Biomedical Engineering (iCBBE), 2010

@inproceedings{fan2010optimized,

   title={Optimized GPU Framework for Ultrasound Color Flow Imaging},

   author={Fan, Z. and Shi, D. and Liu, D.C.},

   booktitle={Bioinformatics and Biomedical Engineering (iCBBE), 2010 4th International Conference on},

   pages={1–4},

   organization={IEEE},

   year={2010}

}

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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 a frame rate of 300 fps from the Doppler signal, in which the number of scan lines is 44, the number of samples along the axial line is 510 and ensemble size is 16.
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