Detection of individual microbubbles using wavelet transform based on a theoretical bubble oscillation model

  • Authors:

  • Yujin Zong;Bin Li;Mingxi Wan;Supin Wang

  • Affiliations:

  • Department of Biomedical engineering, Key Laboratory of Biomedical Information Engineering of Ministry of Education, Xi'an Jiaotong University, Xi'an, China;Department of Biomedical engineering, Key Laboratory of Biomedical Information Engineering of Ministry of Education, Xi'an Jiaotong University, Xi'an, China;Department of Biomedical engineering, Key Laboratory of Biomedical Information Engineering of Ministry of Education, Xi'an Jiaotong University, Xi'an, China;Department of Biomedical engineering, Key Laboratory of Biomedical Information Engineering of Ministry of Education, Xi'an Jiaotong University, Xi'an, China

  • Venue:
  • ICNC'06 Proceedings of the Second international conference on Advances in Natural Computation - Volume Part II
  • Year:
  • 2006

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Abstract

Detecting individual microbubbles is important for the quantification of the amount of bubbles in the tissues, determination of microvascular volume and targeted microbubble imaging. We took the advantage of a theoretical bubble oscillation model to construct a matched wavelet, i.e. bubble wavelet as mother wavelet to detect individual microbubble using wavelet transform. The experimental echoes with different levels of added noises were processed. The results showed significant improvement even for an Echo-Noise-Ratio (ENRin) of -20 dB and the spatial location demonstrated very close agreement with the original experimental echo. This technique was much better than those based on harmonic analysis especially under the circumstance of short pulse insonation.