A compressed-sensing approach for ultrasound imaging

Adrien Besson, Rafael E. Carrillo, Dimitris Perdios, Marcel Arditi, Yves Wiaux, Jean-Philippe Thiran

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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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.
Original languageEnglish
Title of host publicationProceedings of SPARS 2017
Number of pages2
Publication statusPublished - 2017
Event6th Signal Processing with Adaptive Sparse Structured Representations workshop 2017 - Lisbon, Portugal
Duration: 5 Jun 20178 Jun 2017


Workshop6th Signal Processing with Adaptive Sparse Structured Representations workshop 2017
Abbreviated titleSPARS 2017


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