2010JOURNAL OF ELECTRONICS INFORMATION TECHNOLOGYOpen access

Ultrasounic Imaging Based on Coded Exciting Technology and Adaptive Beamforming

Chichao Zheng, Hu Peng

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Abstract

与传统的延时叠加(DAS)波束形成的成像方法相比,Capon算法可以有效地提高医学超声成像的横向分辨率,但不能提高成像的对比度。该文提出一种新的成像方法Chirp_Capon算法,即将超声编码发射技术与Capon算法相结合,利用编码信号优异的相关特性来弥补Capon算法在对比度上的不足,从而得到了较好的成像结果。仿真结果表明相对于Capon算法,该算法不仅具有较高横向分辨率,而且可以有效提高图像的对比度和信噪比。

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What this paper is about

与传统的延时叠加(DAS)波束形成的成像方法相比,Capon算法可以有效地提高医学超声成像的横向分辨率,但不能提高成像的对比度。该文提出一种新的成像方法Chirp_Capon算法,即将超声编码发射技术与Capon算法相结合,利用编码信号优异的相关特性来弥补Capon算法在对比度上的不足,从而得到了较好的成像结果。仿真结果表明相对于Capon算法,该算法不仅具有较高横向分辨率,而且可以有效提高图像的对比度和信噪比。

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Available abstract

与传统的延时叠加(DAS)波束形成的成像方法相比,Capon算法可以有效地提高医学超声成像的横向分辨率,但不能提高成像的对比度。该文提出一种新的成像方法Chirp_Capon算法,即将超声编码发射技术与Capon算法相结合,利用编码信号优异的相关特性来弥补Capon算法在对比度上的不足,从而得到了较好的成像结果。仿真结果表明相对于Capon算法,该算法不仅具有较高横向分辨率,而且可以有效提高图像的对比度和信噪比。

Key concepts: Capon, Beamforming, Adaptive beamformer, Chirp, Computer science, Speech recognition, Telecommunications, Physics

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