With the introduction of very dense sensor arrays in ultrasound (US) imaging, data transfer rate and data storage became a bottleneck in ultrasound system design. To reduce the amount of sampled channel data, we propose to use a low-rank and joint-sparse model to represent US signals and exploit the correlations between adjacent receiving channels. Results show that the proposed method is adapted to the ultrasound signals and can recover high quality image approximations from as low as 10% of the samples.
Original languageEnglish
Title of host publicationin Proceedings of iTWIST'18
Subtitle of host publicationinternational Traveling Workshop on Interactions between low-complexity data models and Sensing Techniques, CIRM
Place of PublicationMarseille, France
Pages21-23
Number of pages3
Publication statusPublished - 23 Nov 2018
EventInternational Traveling Workshop on Interactions between low-complexity data models and Sensing Techniques - CIRM, Marseille, France
Duration: 21 Nov 201823 Nov 2018
Conference number: 2018
https://sites.google.com/view/itwist18

Workshop

WorkshopInternational Traveling Workshop on Interactions between low-complexity data models and Sensing Techniques
Abbreviated titleiTWIST'18
CountryFrance
CityMarseille
Period21/11/1823/11/18
Internet address

    Research areas

  • Electrical Engineering and Systems Science, Signal Processing

ID: 40126457