WASET
	@article{(Open Science Index):https://publications.waset.org/pdf/1343,
	  title     = {Retrospective Synthetic Focusing with Correlation Weighting for Very High Frame Rate Ultrasound},
	  author    = {Chang-Lin Hu and  Yao-You Cheng and  Meng-Lin Li},
	  country	= {},
	  institution	= {},
	  abstract     = {The need of high frame-rate imaging has been triggered by the new applications of ultrasound imaging to transient elastography and real-time 3D ultrasound. Using plane wave excitation (PWE) is one of the methods to achieve very high frame-rate imaging since an image can be formed with a single insonification. However, due to the lack of transmit focusing, the image quality with PWE is lower compared with those using conventional focused transmission. To solve this problem, we propose a filter-retrieved transmit focusing (FRF) technique combined with cross-correlation weighting (FRF+CC weighting) for high frame-rate imaging with PWE. A restrospective focusing filter is designed to simultaneously minimize the predefined sidelobe energy associated with single PWE and the filter energy related to the signal-to-noise-ratio (SNR). This filter attempts to maintain the mainlobe signals and to reduce the sidelobe ones, which gives similar mainlobe signals and different sidelobes between the original PWE and the FRF baseband data. Normalized cross-correlation coefficient at zero lag is calculated to quantify the degree of similarity at each imaging point and used as a weighting matrix to the FRF baseband data to further suppress sidelobes, thus improving the filter-retrieved focusing quality.
},
	    journal   = {International Journal of Biomedical and Biological Engineering},
	  volume    = {6},
	  number    = {5},
	  year      = {2012},
	  pages     = {177 - 179},
	  ee        = {https://publications.waset.org/pdf/1343},
	  url   	= {https://publications.waset.org/vol/65},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 65, 2012},
	}