Time reversal microwave breast imaging for contrast-enhanced tumor classification

P Kosmas, S Laranjeira, J H Dixon, X Li, Y Chen

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

8 Citations (Scopus)

Abstract

This paper studies the decomposition of the time reversal operator (DORT, by the French acronym) technique for microwave breast lesion classification. We apply the finitedifference time-domain (FDTD) method to a realistic numerical breast phantom where lesion-like targets are artificially introduced, and obtain the multistatic data matrix (MDM) for a particular antenna array configuration. Then, the singular value decomposition (SVD) of this matrix is derived for different targets, which represent malignant and benign lesions. We show that the singular value spectrum can assist in classifying these targets as malignant or benign, especially in the case where contrast-enhanced agents can be employed to allow the analysis of differential backscatter data.
Original languageEnglish
Title of host publication2010 Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
Place of PublicationPiscataway, N.J.
PublisherIEEE
Pages708 - 711
Number of pages4
VolumeN/A
EditionN/A
ISBN (Print)9781424441242
DOIs
Publication statusPublished - 2010
Event33rd Annual International Conference of the IEEE Engineering-in-Medicine-and-Biology-Society (EMBC 11) - Boston, MA
Duration: 30 Aug 20114 Sept 2011

Publication series

Name2010 ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY (EMBC)

Conference

Conference33rd Annual International Conference of the IEEE Engineering-in-Medicine-and-Biology-Society (EMBC 11)
CityBoston, MA
Period30/08/20114/09/2011

Keywords

  • Algorithms
  • Breast Neoplasms
  • Contrast Media
  • Diagnostic Imaging
  • Female
  • Humans
  • Image Enhancement
  • Image Interpretation, Computer-Assisted
  • Microwaves
  • Phantoms, Imaging
  • Reproducibility of Results
  • Sensitivity and Specificity

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