Ultrasound image reconstruction from compressed measurements using approximate message passing

J. H. Kim, A. Basarab, P. R. Hill, D. R. Bull, D. Kouamé, A. Achim

Research output: Chapter in Book/Report/Conference proceedingConference Contribution (Conference Proceeding)

3 Citations (Scopus)
312 Downloads (Pure)

Abstract

In this paper we propose a novel framework for compressive sampling reconstruction of biomedical ultrasonic images based on the Approximate Message Passing (AMP) algorithm. AMP is an iterative algorithm that performs image reconstruction through image denoising within a compressive sampling framework. In this work, our aim is to evaluate the merits of several combinations of a denoiser and a transform domain, which are the two main factors that determine the recovery performance. In particular, we investigate reconstruction performance in the spatial, DCT, and wavelet domains. We compare the results with existing reconstruction algorithms already used in ultrasound imaging and quantify the performance improvement.

Original languageEnglish
Title of host publication2016 24th European Signal Processing Conference, EUSIPCO 2016
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages557-561
Number of pages5
ISBN (Electronic)9780992862657
DOIs
Publication statusPublished - 1 Dec 2016
Event24th European Signal Processing Conference, EUSIPCO 2016 - Budapest, Hungary
Duration: 28 Aug 20162 Sep 2016

Conference

Conference24th European Signal Processing Conference, EUSIPCO 2016
CountryHungary
CityBudapest
Period28/08/162/09/16

Keywords

  • AMP
  • Compressive sampling
  • Image denoising
  • IRLS
  • Nonconvex optimization
  • Ultrasonic images

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