CHEBYSHEV FILTER APPLIED TO AN INVERSION TECHNIQUE FOR BREAST TUMOUR DETECTION

Abstract

Microwave imaging has been extensively studied in the past several years as a new technique for early stage breast cancer detection. The rationale of microwave imaging for breast tumour detection is significant contrast in the dielectric properties of normal tissue and malignant tumours. However, in practice noise present from the environments during screening/examination degrades the quality of the image. Inaccurate reconstructed image caused false/misleading interpretation of the image which leads to inappropriate diagnose or treatment to the patient. In the simulation works, noise is added to imitate the actual environment scenario. The two-dimensional (2D) object that identical to breast model is developed using numerical simulation to imitate the breast model. A filter is integrated with an iterative inversion technique for breast tumour detection to eliminate the noise. To assess the effectiveness of this approach, we consider the reconstruction of the electrical parameter profiles of 2D objects from measurements of the transient total electromagnetic field data contaminated with noise. Additive white Gaussian noise is utilized to mimic the effect of random processes that occur in the nature. This paper presents the filter settings and characteristics that affect the reconstruction of the image in order to obtain the most reliable and closer to the actual image. Selection of filter settings or design is important in order to achieve desired signal, most accurate image and provide reliable information of the object. Chebyshev low pass filter is applied in the Forward-Backward Time-Stepping (FBTS) algorithm to filter the noisy data and to improve the quality of reconstructed image.