Authors - Sangeeta Singha, Lalhriatpuii, Banani Basu, Arnab Nandi Abstract - This research presents a microwave-based breast cancer detection framework that leverages the Specific Absorption Rate (SAR) of an Ultra-Wideband (UWB) patch antenna, operating between 3.1 and 10.6 GHz. By positioning an antenna array on opposite sides of a breast phantom and rotating it, the system records SAR distributions as 2D input images. To isolate pathological features, image segmentation is performed on these 2D data samples to distinguish between healthy, benign and malignant tissue. These processed images are then classified using a ResNeXt architecture integrated with a Spatial Attention Module (SAM) to enhance tumor detection. Experimental results demonstrate the efficacy of this attention-driven approach, as the integration of the SAM improved classification accuracy to 98.44%.
