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Investigation of compressive sensing approach in microwave brain imaging system for brain-tumor detection

Published online by Cambridge University Press:  15 December 2025

Tavangar Najafi ,
Seyed Ali Emamghorashi Open the ORCID record for Seyed Ali Emamghorashi [Opens in a new window]  and
Azar Mahmoodzadeh
Tavangar Najafi
Affiliation:
Department of Electrical Engineering, Islamic Azad University, Shiraz Branch, Shiraz, Iran
Seyed Ali Emamghorashi*
Affiliation:
Department of Electrical Engineering, Islamic Azad University, Fasa Branch, Fasa, Iran
Azar Mahmoodzadeh
Affiliation:
Department of Electrical Engineering, Islamic Azad University, Shiraz Branch, Shiraz, Iran
*
Corresponding author: Seyed Ali Emamghorashi; Email: Aemamghorashi@iaufasa.ac.ir
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Abstract

In this paper, we present an ultra-fast technique for brain tumor detection in microwave brain imaging systems based on compressive sensing (CS). To achieve this, we designed an elliptical array-based microwave imaging system by simulating sixteen elements of modified bowtie antennas in the CST medium around a multi-layer head phantom. Additionally, we designed an appropriate matching medium to radiate in the desired band from 1 to 4 GHz. The algorithm section of our technique involves pre-processing steps for calibration, a processing step to create a two-dimensional image of the received signals, and a post-processing step for CS. In the processing section, we used a confocal image-reconstructing method based on delay and sum and delay, multiply, and sum beam-forming algorithms. Finally, we applied a new CS technique that includes an L1-norm convex optimization method to reconstruct low-dimension images from the original reconstructed images. We present simulated results to validate the effectiveness of our proposed method for precisely localizing the tumor target in a human full head phantom. The simulated results demonstrate that by using our proposed CS method, the image reconstruction processing time decreased to 63% and the compressed image size reduced to 25% of the original image.

Keywords

brain tumor detectioncompressive sensingconfocal image reconstruction algorithmmicrowave head imaging system

Information

Type
Research Paper
Information
International Journal of Microwave and Wireless Technologies , First View , pp. 1 - 7
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Copyright
© The Author(s), 2025. Published by Cambridge University Press in association with The European Microwave Association.

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