Microwave head imaging systems for early brain tumor detection: antenna designs and emerging substrates
Year: 2025
Type: article
Abstract: • Brain tumors are presented with emphasis on their types, diagnostic challenges, and the necessity of early detection. • Antenna technology in medical imaging is reviewed with focus on its evolution, role in brain tumor detection, and associated advantages and limitations. • Key antenna design considerations for brain tumor detection are outlined, including frequency selection, size and configuration, material choice, and signal processing integration. • Future directions and challenges are highlighted, addressing microwave imaging antennas, ultra-wideband systems, RF coils for MRI, and other emerging technologies. Early detection of brain tumors is essential for successful treatment and better patient outcomes. Traditional imaging methods like X-rays, MRIs, CT scans, and PET scans have been important in detecting brain tumors, but they are expensive with many drawbacks and areas where access is limited. Antenna-based method has recently emerged as a practical alternative for real-time, non-invasive detection of brain tumors. This paper explores different antennas and various types of substrates that are adaptable to human sensitive tissues for detecting brain tumors. This review highlights the antenna working principles, and the advantages and challenges associated with each type. The effectiveness of several antenna-based methods in medical diagnostics, including microwave imaging and ultra-wideband (UWB) systems, is discussed. To assess their impact on detection accuracy, essential factors such as penetration depth, resolution, operating frequency, and antenna design are considered. The integration of antennas with machine learning and signal processing techniques is investigated.
Source: MethodsX
Authors: Jinu Mathew, Osamah Ibrahim Khalaf, Navin M George, Ancy Michel, Neethan Elizabeth Abraham, Deema Mohammed Alsekait, Sharf Alzu’bi, Diaa Salama AbdElminaam
Language: English
Subfield: Biomedical Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $1,260
Award: G5235441952
OpenAlex ID: W4416401963
