STRUCTURALLY RANDOM FOURIER DOMAIN COMPRESSIVE SAMPLING AND FREQUENCY DOMAIN BEAMFORMING FOR ULTRASOUND IMAGING

被引:0
|
作者
Foroozan, Foroohar [1 ]
Yousefi, Rozhin [2 ]
Sadeghi, Parastoo [3 ]
Kolios, Michael C. [4 ]
机构
[1] Analog Devices Inc, Toronto, ON, Canada
[2] Univ Toronto, IBBME, Toronto, ON, Canada
[3] Australian Natl Univ, Canberra, ACT, Australia
[4] Ryerson Univ, Toronto, ON, Canada
基金
加拿大自然科学与工程研究理事会;
关键词
Compressive Sensing; Structurally Random Matrices; Beamforming; and Ultrasound Imaging; SIGNAL RECONSTRUCTION; SPARSITY; SINUSOIDS;
D O I
暂无
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Advances in ultrasound technology have fueled the emergence of Point-Of-Care Ultrasound (PoCU) imaging, including improved ease-of-use, superior image quality, and lower cost ultrasound. One of the approaches that can make the adoption of PoCU universal is to make the data acquisition module as simple as a "stethoscope" while further processing and image construction can be done using cloud-based processors. Toward this goal, we use Structurally Random Matrices (SRM) for compressive sensing of ultrasound data, Fourier sparsifying matrix for recovery in 1D, and frequency domain approach for 2D ultrasound image reconstruction. This approach is demonstrated through wire phantom and in vivo carotid arteries data from ultrasound system using 25%, 12.5%, and 6.25% of the full data rate and ultrasound images of similar perceived quality quantified by Structural Similarity Index Metric (SSIM).
引用
收藏
页码:2111 / 2115
页数:5
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