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Effect of lesion morphology on microwave signature in 2-D ultra-wideband breast imaging

Effect of lesion morphology on microwave signature in 2-D ultra-wideband breast imaging

Chen, Y., Gunawan, E., Low, K. S., Wang, S. C., Soh, C. B. and Putti, T. C. (2008) Effect of lesion morphology on microwave signature in 2-D ultra-wideband breast imaging. IEEE Transactions on Biomedical Engineering, 55 (8). pp. 2011-2021. ISSN 0018-9294 (doi:10.1109/TBME.2008.921136)

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Abstract

This paper studies the possibility of distinguishing between benign and malignant masses by exploiting the morphology-dependent temporal and spectral characteristics of their microwave backscatter response in ultra-wideband breast cancer detection. The spiculated border profiles of 2-D breast masses are generated by modifying the baseline elliptical rings based upon the irregularity of their peripheries. Furthermore, the single- and multilayer lesion models are used to characterize a distinct mass region followed by a sharp transition to background, and a blurred mass border exhibiting a gradual transition to background, respectively. Subsequently, the complex natural resonances (CNRs) of the backscatter microwave signature can be derived from the late-time target response and reveal diagnostically useful information. The fractional sequence CLEAN algorithm is proposed to estimate the lesions' delay intervals and identify the late-time responses. Finally, it is shown through numerical examples that the locations of dominant CNRs are dependent on the lesion morphologies, where 2-D computational breast phantoms with single and multiple lesions are investigated. The analysis is of potential use for discrimination between benign and malignant lesions, where the former usually possesses a better-defined, more compact shape as opposed to the latter.

Item Type: Article
Uncontrolled Keywords: cancer detection, dielectric-properties, tissues, time, tumors, shape, resonances, scattering, algorithm
Subjects: T Technology > T Technology (General)
R Medicine > R Medicine (General)
T Technology > TK Electrical engineering. Electronics Nuclear engineering
R Medicine > RC Internal medicine
Pre-2014 Departments: School of Engineering
School of Engineering > Department of Computer & Communications Engineering
Related URLs:
Last Modified: 14 Oct 2016 09:07
Selected for GREAT 2016: None
Selected for GREAT 2017: None
Selected for GREAT 2018: None
URI: http://gala.gre.ac.uk/id/eprint/2640

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