Performance of ultra‐wide band DCBLNA with suspended strip line radiator for human breast cancer diagnosis medical imaging application

Medical imaging techniques, including X-ray mammography, ultrasound, and magnetic resonance imaging, play a crucial role in the timely identification and monitoring of breast cancer. However, these conventional imaging modalities have their limitations, and there is a need for a more accurate and sensitive alternative. Microwave imaging has emerged as a promising technique for breast cancer detection due to its non-ionizing, non-invasive, and cost-effective nature. Recent advancements in microwave imaging and sensing techniques have opened up new possibilities for the early diagnosis and treatment of breast cancer. By combining microwave sensing with machine learning techniques, microwave imaging approaches can rapidly and affordably identify and classify breast tumors. This manuscript provides a comprehensive overview of the latest developments in microwave imaging and sensing techniques for the early detection of breast cancer. It discusses the principles and applications of microwave imaging and highlights its advantages over conventional imaging modalities. The manuscript also delves into integrating machine learning algorithms to enhance the accuracy and efficiency of microwave imaging in breast cancer detection.

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Performance of ultra‐wide band DCBLNA with suspended strip line radiator for human breast cancer diagnosis medical imaging application

Cited by 2 publications

References 23 publications

A Self-Packaging Comb Spectrum Generator Based on Substrate Integrated Suspension Line

A Self-Packaging Comb Spectrum Generator Based on Substrate Integrated Suspension Line

Microwave Imaging and Sensing Techniques for Breast Cancer Detection

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