Effect of phantom orientation angle on antenna sensor response in agar-based homogeneous phantom for abnormal breast tissue detection

Microwave sensing Breast phantom antenna sensor Resonance frequency shift Reflection coefficient (S11)

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Breast cancer remains a major global health concern; therefore, early detection plays a crucial role in reducing its mortality rates. Conventional imaging techniques, such as mammography, have limitations including ionizing radiation exposure and reduced sensitivity in dense breast tissues. Microwave-based sensing has emerged as a promising alternative due to its non-ionizing nature, relatively low cost, and sensitivity to dielectric property contrasts between normal and malignant tissues. This study aims to investigate the effect of phantom orientation angle on the response of an antenna-based microwave sensor for abnormal breast tissue detection. An agar-based homogeneous breast phantom is utilized, with tumor inclusion modeled as regions of different dielectric properties. Measurements are conducted using a Vector Network Analyzer (VNA) over a frequency range of 2–6 GHz, with four orientation angles (0°, 90°, 180°, and 270°). The reflection coefficient (S11) is analyzed to observe variations in electromagnetic response under different conditions. The results indicate that tumor presence causes measurable shifts in resonance frequency and variations in the reflection coefficient (S11). Larger tumors produce greater frequency shifts due to higher dielectric contrast. Furthermore, the orientation angle significantly affects detection sensitivity, which is attributed to the antenna radiation pattern and spatial interaction between electromagnetic waves and the phantom. In conclusion, this study demonstrates that both tumor size and phantom orientation influence antenna sensor response. The novelty of this work lies in the incorporation of orientation-based analysis, providing new insight into spatial electromagnetic interactions and enhancing the potential of microwave sensing systems for accurate and non-invasive breast cancer detection.