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An overview of radar based ultra wideband breast cancer detection algorithms

An overview of radar based ultra wideband breast cancer detection algorithms

Teo, Jianqi, Chen, Yifan, Soh, Cheong Boon, Gunawan, Erry, Low, Kay Soon, Putti, Thomas Choudary and Wang, Shih-Chang (2010) An overview of radar based ultra wideband breast cancer detection algorithms. International Journal of Ultra Wideband Communications and Systems, 1 (4). pp. 273-281. ISSN 1758-728X (Print), 1758-7298 (Online) (doi:https://doi.org/10.1504/IJUWBCS.2010.034308)

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Abstract

Breast cancer is the most common cancer in women in almost all countries around the world, and is one of the most common non-infective causes of death. Mammography, which uses ionising radiation, is the only early breast cancer screening technique proven to reduce breast cancer mortality in randomised controlled clinical trials. However, screening mammography is expensive, technically demanding and requires a high level of clinical expertise. It cannot be performed in general medical clinical settings readily. Ultra wideband (UWB) or microwave breast screening has the potential to be a safe, accurate and easy-to-use technique for breast disease detection that is more effective than routine clinical palpation or breast self-examination. Ultra wideband breast cancer detection algorithms have been researched by several groups for over a decade, with numerous algorithms reported. This paper serves to give an overview of existing algorithms for UWB breast cancer detection.

Item Type: Article
Uncontrolled Keywords: breast lesions, lesion classification, ultra wideband systems, radar based UWB, breast cancer detection, microwave breast screening, UWB breast screening
Subjects: T Technology > T Technology (General)
T Technology > TK Electrical engineering. Electronics Nuclear engineering
Faculty / Department / Research Group: Faculty of Engineering & Science
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/7681

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