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Multifrequency Microwave Imaging for Brain Stroke Detection

Lulu Wang1,*

1 Department of Biomedical Engineering, School of Instrument Science and Opto-electronics Engineering, Hefei University of Technology, Hefei, 230009, China

* Corresponding Author: Lulu Wang. Email: email; email

Molecular & Cellular Biomechanics 2020, 17(1), 33-40. https://doi.org/10.32604/mcb.2019.07165

Abstract

CT and MRI are often used in the diagnosis and monitoring of stroke. However, they are expensive, time-consuming, produce ionizing radiation (CT), and not suitable for continuous monitoring stroke. Microwave imaging (MI) has been extensively investigated for identifying several types of human organs, including breast, brain, lung, liver, and gastric. The authors recently developed a holographic microwave imaging (HMI) algorithm for biological object detection. However, this method has difficulty in providing accurate information on embedded small inclusions. This paper describes the feasibility of the use of a multifrequency HMI algorithm for brain stroke detection. A numerical system, including HMI data collection model and a realistic head model, was developed to demonstrate the proposed method for imaging of brain tissues. Various experiments were carried out to evaluate the performance of the proposed method. Results of experiments carried out using multifrequency HMI have been compared with the results obtained from single frequency HMI. Results showed that multifrequency HMI could detect strokes and provide more accurate results of size and location than the single frequency HMI algorithm.

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APA Style
Wang, L. (2020). Multifrequency microwave imaging for brain stroke detection. Molecular & Cellular Biomechanics, 17(1), 33-40. https://doi.org/10.32604/mcb.2019.07165
Vancouver Style
Wang L. Multifrequency microwave imaging for brain stroke detection. Mol Cellular Biomechanics . 2020;17(1):33-40 https://doi.org/10.32604/mcb.2019.07165
IEEE Style
L. Wang, "Multifrequency Microwave Imaging for Brain Stroke Detection," Mol. Cellular Biomechanics , vol. 17, no. 1, pp. 33-40. 2020. https://doi.org/10.32604/mcb.2019.07165

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cc Copyright © 2020 The Author(s). Published by Tech Science Press.
This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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