ABDUL-SATTAR, ZUBAIDA (2012) Experimental Analysis on Effectiveness of Confocal Algorithm for Radar Based Breast Cancer Detection. Masters thesis, Durham University.
|PDF - Accepted Version|
Breast cancer is one of the most commonly diagnosed cancers in females in UK . Early breast cancer detection which has recently been gaining a lot of consideration within the research community and the most important for a quick and effective treatment of the cancer is early detection. UWB radar based microwave imaging for early breast cancer detection is one of the most promising and attractive screening techniques currently under research. This technique offers several advantages such as low cost, better patient comfort, non-ionising and non-invasive radiation compared to X-Ray mammography. In this technique the breast is illuminated from various points with short UWB microwave pulse(s) and the collected backscattered energy is then processed to identify the presence and location of the tumour.
In this thesis experimental measurement of the reflection coefficient in complex frequency domain is obtained from Vector Network Analyzer (VNA E5071) when the antenna is exposed to the environment and when the antenna is exposed to breast phantom. The tumor is simulated with different materials to investigate the effectiveness of the Confocal Microwave Imaging Algorithm for breast cancer detection. In addition, we used the materials at different depths to determine the effect of antenna distance to that of the tumor response.
The Confocal Microwave Imaging (CMI) Algorithm for breast cancer detection is an easy and robust technique for tumor detection, which is used to approximate the precise location of the tumor. CMI is based on illuminating the breast with the UWB pulse from different antenna locations. The relative arrival times & amplitudes of the backscatter signals is used to estimate the location of the tumor. We applied the Confocal Algorithm in this study to the numerical data generated with the VNA and analyzed the results with different material(s) as tumor at different depth to verify its ability to estimate a tumor response.
|Item Type:||Thesis (Masters)|
|Award:||Master of Science|
|Faculty and Department:||Faculty of Science > Engineering and Computing Science, School of (2008-2017)|
|Copyright:||Copyright of this thesis is held by the author|
|Deposited On:||16 May 2012 14:31|