Unidirectional wideband antenna with improved circular parasitic element for microwave breast imaging applications
Early cancer detection, especially in the breast, is crucial due to its asymptomatic nature. Intricate measurement techniques are essential for accurate cancer identification, with the antenna being a key element. Ideally, it should be flexible, unidirectional, wideband, lightweight, and compact com...
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| Format: | Thesis |
| Language: | English English |
| Published: |
2024
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| Online Access: | http://eprints.utem.edu.my/id/eprint/28565/ https://plh.utem.edu.my/cgi-bin/koha/opac-detail.pl?biblionumber=124407 |
| Abstract | Abstract here |
| Summary: | Early cancer detection, especially in the breast, is crucial due to its asymptomatic nature. Intricate measurement techniques are essential for accurate cancer identification, with the antenna being a key element. Ideally, it should be flexible, unidirectional, wideband, lightweight, and compact compared to previous research, improving antenna performance for precise measurements in breast cancer detection using a radar-based approach. The research aims to create a unidirectional, interference-avoiding, wideband antenna using flexible material. It presents a co-planar waveguide (CPW) wideband antenna with felt material for the 3 GHz to 7 GHz frequency range, incorporating a double-layer reflector for enhanced unidirectionality and flexibility. To confirm the antenna's performance, a model of a breast (breast phantom) was created and assessed, achieving a safe SAR level below 1.65 W/kg at a 10 mm distance. In microwave breast cancer detection, strict limitations on antenna size exist to accommodate the limited breast area, requiring a maximum typical diameter for unidirectional radiation and signal distortion suppression. The proposed antenna, enhanced by a double-reflector element, exhibited improved performance, broad 3.06 GHz to 7.0 GHz bandwidth, with measurement result of directivity (6.98 dBi), FBR (9.81 dB), and gain (5.44 dBi).The antenna and breast phantom, connected to a vector network analyzer, utilized a MATLAB algorithm (modified Delay and Sum imaging) for signal processing and image reconstruction. They successfully detected five diferent sizes of breast cancer with outstanding measurement responses, including cancers as small as 1milimeter, consistent with simulation results. |
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