Morphological component analysis for sparse regularization in plane wave imaging

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

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

2 Citations (Scopus)
32 Downloads (Pure)

Abstract

Classical ultrasound image reconstruction mainly relies on the well-known delay-and-sum (DAS) beamforming for its simplicity and real-time capability. Sparse regularization methods propose an alternative to DAS which lead to a better inversion of the ill-posed problem resulting from the acoustic wave propagation. In the following work, a new sparse regularization method is proposed which includes a component-based modelling of the radio-frequency images as well as a point-spread-function-adaptive sparsity prior. The proposed method, evaluated on the PICMUS dataset,outperforms the classical DAS in terms of contrast and resolution.

Original languageEnglish
Title of host publication2016 IEEE International Ultrasonics Symposium (IUS)
PublisherIEEE
ISBN (Electronic)9781467398978
DOIs
Publication statusPublished - 3 Nov 2016
Event2016 IEEE International Ultrasonics Symposium - VINCI Convention Center, Tours, France
Duration: 18 Sep 201621 Sep 2016

Publication series

NameIEEE International Ultrasonics Symposium : proceedings
PublisherIEEE
ISSN (Print)1948-5727

Conference

Conference2016 IEEE International Ultrasonics Symposium
Abbreviated titleIUS 2016
CountryFrance
CityTours
Period18/09/1621/09/16

Keywords

  • Compressed sensing
  • Plane wave
  • Sparse regularization

ASJC Scopus subject areas

  • Acoustics and Ultrasonics

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