Fusion of ultrasound harmonic imaging with clutter removal using sparse signal separation

Javier S. Turek, Jeremias Sulam, Michael Elad, Irad Yavneh

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

In ultrasound, second harmonic imaging is usually preferred due to the higher clutter artifacts and speckle noise common in the first harmonic image. Typical ultrasound use either one or the other image, applying corresponding filters for each case. In this work we propose a method based on a joint sparsity model that fuses the first and second harmonic images while performing clutter mitigation and noise reduction. Our approach, Fused Morphological Component Analysis (FMCA), uses two adaptive dictionaries for characterizing the clutter components in each image, and a common dictionary for the tissue representation. Our results indicate that the obtained images contain less clutter artifacts, less speckle noise and as such enjoy of the benefits of both harmonic input images.

Original languageEnglish
Title of host publication2015 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2015 - Proceedings
Pages793-797
Number of pages5
ISBN (Electronic)9781467369978
DOIs
StatePublished - 4 Aug 2015
Event40th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2015 - Brisbane, Australia
Duration: 19 Apr 201424 Apr 2014

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Volume2015-August

Conference

Conference40th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2015
Country/TerritoryAustralia
CityBrisbane
Period19/04/1424/04/14

Keywords

  • Artifact reduction
  • harmonic imaging
  • image fusion
  • morphological component analysis
  • signal separation

All Science Journal Classification (ASJC) codes

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

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