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Adaptive artifact removal for selective multistatic microwave breast imaging signals

Research output: Contribution to a Journal (Peer & Non Peer)Articlepeer-review

22 Citations (Scopus)

Abstract

Microwave imaging is one of the most promising alternative breast imaging modalities. Early-stage artifact removal is an important signal processing component of a microwave breast imaging system. In this paper, a monostatic artifact removal algorithm is extended to remove the early-stage artifact from multistatic radar signals. The multistatic radar signals exhibit greater variation in the early-stage artifact due to varying propagation paths between transmitting and receiving antennas. This variation makes it more challenging to estimate and remove the artifact compared to the monostatic signals. This paper proposes an entropy-based adaptive method to group signals with similar artifacts and then remove the artifact from each group separately using a hybrid artifact removal algorithm. The efficacy of the proposed algorithm has been demonstrated by imaging anatomically and dielectrically realistic 3D numerical breast phantoms. (C) 2017 Elsevier Ltd. All rights reserved.
Original languageEnglish (Ireland)
Pages (from-to)93-100
Number of pages8
JournalBiomedical Signal Processing and Control
Volume34
DOIs
Publication statusPublished - 1 Apr 2017

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • Breast cancer
  • Microwave imaging
  • Multistatic artifact removal
  • Skin subtraction
  • Skin-artifact removal
  • Ultra wideband radar

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