Wavelet de-noising based microwave imaging for brain cancer detection

Haoyu Zhang*, Tughrul Arslan, Brian Flynn

*Corresponding author for this work

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


In microwave imaging for brain cancer detection, signals are generally degraded by noise. In this paper, we investigate the use of Discrete Wavelet Transform (DWT) based signal processing to improve the noise performance of an UWB based microwave imaging system for brain cancer detection. To test the noise suppression properties of the DWT, firstly, Gaussian white noise is added to the received pulse in a simulated microwave imaging system, such that the signal-to-noise ratios (SNRs) are 60dB and 45dB, respectively. These noisy signals are then processed and de-noised using the DWT. The de-noised signals are used to create cross-sectional images of a cancerous brain model, with the tumour highlighted. These resulting images demonstrate the validity of a DWT based de-noising method for brain cancer detection. © 2013 IEEE.

Original languageEnglish
Title of host publication2013 Loughborough Antennas and Propagation Conference, LAPC 2013
EditorsRM Edwards
Place of PublicationNEW YORK
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Number of pages4
ISBN (Print)9781479900916
Publication statusPublished - 1 Dec 2013
EventLoughborough Antennas and Propagation Conference (LAPC) - Loughborough, Loughborough, Leicestershire, United Kingdom
Duration: 11 Nov 201312 Nov 2013


ConferenceLoughborough Antennas and Propagation Conference (LAPC)
Country/TerritoryUnited Kingdom
CityLoughborough, Leicestershire


  • Brain cancer detection
  • DWT
  • Microwave imaging
  • wavelet de-noising


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