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conference paper not in proceedings

A compressed-sensing approach for ultrasound imaging

Besson, Adrien Georges Jean  
•
Carrillo, Rafael E.
•
Perdios, Dimitris  
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2017
Signal Processing with Adaptive Sparse Structured Representations (SPARS) workshop

Ultrasonography uses multiple piezo-electric element probes to image tissues. Current time-domain beamforming techniques require the signal at each transducer-element to be sampled at a rate higher than the Nyquist criterion, resulting in an extensive amount of data to be received, stored and processed. In this work, we propose to exploit sparsity of the signal received at each transducer-element. The proposed approach uses multiple compressive multiplexers for signal encoding and solves an l1-minimization in the decoding step, resulting in the reduction of 75 % of the amount of data, the number of cables and the number of analog-to-digital converters required to perform high quality reconstruction.

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