Title :
Wavelet de-noising based microwave imaging for brain cancer detection
Author :
Haoyu Zhang ; Arslan, Tughrul ; Flynn, B.
Author_Institution :
Adv. Smart Antenna Technol. Res. Group, Univ. of Edinburgh, Edinburgh, UK
Abstract :
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.
Keywords :
AWGN; brain models; cancer; discrete wavelet transforms; image denoising; medical image processing; microwave imaging; tumours; ultra wideband technology; DWT based denoising method; Discrete Wavelet Transform; Gaussian white noise; UWB based microwave imaging system; brain cancer detection; cancerous brain model; cross-sectional images; noise figure 45 dB; noise figure 60 dB; noise performance; noise suppression properties; noisy signal; received pulse; signal processing; signal-to-noise ratio; simulated microwave imaging; tumour; wavelet denoising; Discrete wavelet transforms; Microwave antennas; Microwave imaging; Microwave theory and techniques; Noise; Tumors; Brain cancer detection; DWT; Microwave imaging; wavelet de-noising;
Conference_Titel :
Antennas and Propagation Conference (LAPC), 2013 Loughborough
Conference_Location :
Loughborough
DOI :
10.1109/LAPC.2013.6711946
