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Time reversal microwave breast imaging for contrast-enhanced tumor classification

Time reversal microwave breast imaging for contrast-enhanced tumor classification

Kosmas, P., Laranjeira, S., Dixon, J.H., Li, X. and Chen, Y. (2010) Time reversal microwave breast imaging for contrast-enhanced tumor classification. In: Engineering in Medicine and Biology Society (EMBC), 2010 Annual International Conference of the IEEE. Institute of Electrical and Electronics Engineers, Inc., Piscataway, NJ, USA, pp. 708-711. ISBN 978-1-4244-4123-5 (print) ISSN 1557-170X (online) (doi:https://doi.org/10.1109/IEMBS.2010.5626158)

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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 finite-difference 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.

Item Type: Conference Proceedings
Title of Proceedings: Engineering in Medicine and Biology Society (EMBC), 2010 Annual International Conference of the IEEE
Additional Information: [1] Included in proceedings of the 32nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBS), held 31 August - 4 September 2010, Buenos Aires, Argentina.
Uncontrolled Keywords: breast, cancer, lesions, microwave imaging, shape
Subjects: R Medicine > RC Internal medicine > RC0254 Neoplasms. Tumors. Oncology (including Cancer)
T Technology > T Technology (General)
Pre-2014 Departments: School of Engineering
School of Engineering > Centre for Innovative Product Development
Related URLs:
Last Modified: 14 Oct 2016 09:19
Selected for GREAT 2016: None
Selected for GREAT 2017: None
Selected for GREAT 2018: None
Selected for GREAT 2019: None
URI: http://gala.gre.ac.uk/id/eprint/7617

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