IMPROVED BEAMFORMING ALGORITHM FOR IMAGING RECONSTRUCTION FOR EARLY BREAST CANCER DETECTION BY UWB

2013 ◽  
Vol 22 (10) ◽  
pp. 1340027 ◽  
Author(s):  
LI XU ◽  
XIA XIAO ◽  
TAKAMARO KIKKAWA

Ultra-wide band (UWB) microwave imaging is a promising method for the breast cancer detection based on the large contrast of electric parameters between the malignant tumor and its surrounded normal organisms. In this paper, a two-dimensional model of the breast organisms is numerically carried by the finite difference time domain (FDTD) method. The dispersion characteristics of the breast media are taken into account by single pole Debye model to approach the actual properties of the breast organism. In this method, a tumor is assumed in the model with two cases. The standard Capon beamforming (SCB) and doubly constrained robust Capon beamforming (DCRCB) algorithm performed to reconstruct the image is described in detail. The tumor can be detected and localized using the proposed algorithm and the result demonstrates a good stability of DCRCB algorithm.

2020 ◽  
Author(s):  
◽  
Ahmed Maher Abed

[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI-COLUMBIA AT REQUEST OF AUTHOR.] Worldwide, breast cancer continues to be the top cause of death among women and the second-leading cause of cancer death after lung cancer. Thus, it has become a great global concern. Years of research on both diagnostic and therapeutic breast cancer detection and imaging using microwave techniques has resulted in a variety of novel approaches and studies. These approaches and studies utilize numerical breast phantoms that model structural complexities, tissue heterogeneity, and dispersive dielectric properties. In this dissertation, a microwave breast cancer detection technique was investigated and Ultra-Wide Band (UWB) radar imaging was used. A UWB antenna was designed and modeled using CST Microwave Studio and was used for Ultra-Wide Band microwave breast cancer detection. A new calibration approach for microwave breast cancer detection was proposed to calibrate the signals before applying the beamforming algorithms. A simulation was also used to validate the proposed techniques. Two signal calibration approaches were proposed to remove the high magnitude clutter from the signals. The two approaches are based on the state-space method Autoregressive Moving Average (ARMA). The first approach is derived from Estimation of Signal Parameters via Rotational Invariance Techniques (ESPRIT). This algorithm is referred to as the Pole Isolation via ESPRIT algorithm (PI-ESPRIT). The second approach is also derived from a previously proposed algorithm for microwave breast cancer detection. Th second calibration algorithm is referred to as the Modified Pole Removal algorithm. The Modified Pole Removal algorithm works to detect tumors, in contrast to the previously proposed algorithm (Pole Removal) that shows a lack of tumor detection. Three beamforming techniques were used to focus the signals onto the voxels through the breast phantom. Another beamforming algorithm was proposed, along with the Transmitting-Receiving Antenna Separation Distance (TRASD), which allows for the reduction of the late time clutter effect and improvement of the Signal to Clutter Ratio (SCR) when using the PI-ESPRIT algorithm. Using CST simulation tool, antennas arrayed around the breast are designed to simulate the transmitting/receiving signals. Numerical phantoms, with complicated structures and dispersive dielectric properties of breast tissue, have been developed with the CST simulation tool for simulating electromagnetic propagation. The received signals are imported into the MATLAB program to investigate the proposed approaches and compare them to conventional approaches. Overall, the results have shown improvement.


2008 ◽  
Vol 2008 ◽  
pp. 1-9 ◽  
Author(s):  
M. Klemm ◽  
I. J. Craddock ◽  
J. A. Leendertz ◽  
A. Preece ◽  
R. Benjamin

We have evaluated a modified delay-and-sum (DAS) beamforming algorithm for breast cancer detection with a microwave radar-based system. The improved DAS algorithm uses an additional weight factor calculated at each focal point to improve image quality. These weights essentially represent the quality of preprocessing and coherent radar operation. Using a multistatic UWB radar system based on a hemispherical antenna array, we present experimental detection of 7 mm and 10 mm phantom tumours. We show that the new proposed DAS algorithm improves signal-to-clutter ratio in focused images by 2.65 dB for 10 mm tumour, and by 4.4 dB for 7 mm tumour.


Author(s):  
Bifta Sama Bari ◽  
Sabira Khatun ◽  
Kamarul Hawari Ghazali ◽  
Md. Moslemuddin Fakir ◽  
Wan Nur Azhani W. Samsudin ◽  
...  

2013 ◽  
Vol 748 ◽  
pp. 525-530
Author(s):  
Jin Zu Ji ◽  
Jing Li

Mono pulse algorithm for confocal microwave imaging (CMI) for breast cancer detection is presented in this paper. All the antennas are used as receiver but only one is also used as transmitter. The transmitted signal is emitted for only once, thus the gross electromagnetic wave energy to the breast is reduced and the diagnosis time can be saved. Two confocal microwave imaging algorithms are presented in this paper: delay-sum-max and delay-production-sum. Both algorithms use the same delayed backscattered signals as the convectional CMI. The difference is how to use the delayed signals to form the image of the scattering intensity. Delay-sum-max method adds the signal together to generate the different value in confocal point via coherent and incoherent addition. Delay-production-sum algorithm products the delayed signal so as to make the assigned value in the confocal point outside the tumor is nearly zero. The image results can be compliment for more confirm diagnosis. Finite-difference time-domain (FDTD) method is used for simulation on 3 models of different tumor arrangements. The results show both methods are effective in detecting single-tumor, while there are some limitations in dealing with multi-tumor.


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