Early breast cancer detection via UWB based on MRI-derived model

Abstract

Breast cancer has been one of the most common diseases which cause many women's death throughout the world. The early breast cancer detection is detecting the tumor when it is at early stage, which could help heal the patients and would not harm the women' s health. It is clear that the best way to control this disease is detecting it at an early stage. Ultra-wide band (UWB) microwave imaging is a promising method for breast cancer detection based on the large contrast of electric parameters between the malignant tumor and its surrounded normal breast organisms. Anatomically realistic computational electromagnetic models are very important tools for testing the feasibility and robustness of image algorithms in early breast cancer detection by UWB microwave imaging. Novel anatomically realistic 2-D and 3-D numerical breast phantoms are proposed for microwave breast cancer detection. These phantoms are derived from the MRIs of the real patients. In those phantoms, the specific tissues and the whole breast are combined with real breast shapes, which are with the higher accuracy. Therefore, a higher accuracy model used for the electromagnetic analysis are created based on the Magnetic Resonance Image (MRI) shown in Fig. 1. And Fig. 2 shows the derived model. The breast tissues such as the skin, glandular tissue, chest wall, and the fatty tissue are all contained in this model. The assumed tumor with a diameter of 4 mm is embedded inside the glandular tissue for this research, and its specific place is x = 71 mm, y = 57 mm. In the study, an antenna array composed by 8 antennas is applied in the detection. During the detection, the problem is the big clutters from normal tissues and the strong backscatter from the breast skin, in which the signal from the tumor is embedded. Currently, one of the most common methods of removing these clutters is using the tumor-free model, from which the detected signal is used as the calibration waveform. Then the tumor response can be obtained by subtracting the calibration waveform from signals detected from the tumor-contained breast model. However, in clinical cases, the tumor-free model cannot be obtained easily as different people has different breast configuration. To overcome the aforementioned problem, a method of directly extracting tumor response signals based on ensemble empirical mode decomposition (EEMD) is proposed for early breast cancer detection by UWB microwave imaging. This method could extract the tumor response directly from the as-detected signals obtained from the tumor-contained breast model. After all the tumor response signals are obtained, the confocal microwave imaging (CMI) algorithm is used for signal processing and image reconstruction to find the position of the breast tumor. To obtain more accurate result, the double constrained robust capon beamforming (DCRCB) algorithm is also proposed for the breast image reconstruction due to its better stability and high SINR. The feasibility and correctness are verified by detecting a 4 mm tumor located inside the glandular region. The imaging result is shown in Fig.3.