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Current Medical Imaging

Editor-in-Chief

ISSN (Print): 1573-4056
ISSN (Online): 1875-6603

Research Article

Ground Penetrating Radar Algorithm to Sense the Depth of Blood Clot in Microwave Head Imaging

Author(s): Lalitha Kandasamy* and Manjula J.

Volume 18, Issue 8, 2022

Published on: 25 March, 2022

Article ID: e140122200241 Pages: 10

DOI: 10.2174/1573405618666220114150216

Price: $65

Abstract

Background: Microwave imaging is one of the emerging non-invasive portable imaging techniques, which uses nonionized radiations to take a detailed view of biological tissues in the microwave frequency range. Brain stroke is an emergency caused by the interruption of the blood supply into parts of the brain, leading to the loss of millions of brain cells. Imaging plays a major role in stroke diagnosis for prompt treatment.

Objective: This work proposes a computationally efficient algorithm called the GPR algorithm to locate the blood clot with a size of 10 mm in microwave images.

Methods: The electromagnetic waves are radiated, and backscattered reflections are received by Antipodal Vivaldi antenna with the parasitic patch (48 mm*21 mm). The received signals are converted to a planar 2D image, and the depth of the blood clot is identified from the B-scan image. The novelty of this work lies in applying the GPR algorithm for the accurate positioning of a blood clot in a multilayered head tissue.

Results: The proposed system is effectively demonstrated using a 3D M.E.M. simulator, and simulated results are verified in a Vector network analyzer (E8363B) with an experimental setup.

Conclusion: This is an alternative safe imaging modality compared to present imaging systems (T.C.T. and MRI).

Keywords: Antipodal vivaldi antenna, microwave head imaging, stroke detection, ground-penetrating radar, depth of blood clot, dielectric properties.

Graphical Abstract
[1]
Munawar Qureshi A, Mustansar Z, Mustafa S. Finite-element analysis of microwave scattering from a three-dimensional human head model for brain stroke detection. R Soc Open Sci 2018; 5(7): 180319.
[http://dx.doi.org/10.1098/rsos.180319] [PMID: 30109085]
[2]
Mohammed BJ, Abbosh AM, Mustafa S, Ireland D. Microwave system for head imaging. IEEE Trans Instrum Meas 2014; 63(1): 117-23.
[http://dx.doi.org/10.1109/TIM.2013.2277562]
[3]
Persson M, Fhager A, Trefná HD, et al. Microwave-based stroke diagnosis making global prehospital thrombolytic treatment possible. IEEE Trans Biomed Eng 2014; 61(11): 2806-17.
[http://dx.doi.org/10.1109/TBME.2014.2330554] [PMID: 24951677]
[4]
Scapaticci R, Tobon J, Bellizzi G, Vipiana F, Crocco L. Design and numerical characterization of a low complexity microwave device for brain stroke monitoring. IEEE Trans Antenn Propag 2018; 66(12): 7328-38.
[http://dx.doi.org/10.1109/TAP.2018.2871266]
[5]
Merunka I, Massa A, Vrba D, Fiser O, Salucci M, Vrba J. Microwave tomography system for methodical testing of human brain stroke detection approaches. Int J Antennas Propag 2019; 2019: 1-9.
[http://dx.doi.org/10.1155/2019/4074862]
[6]
Mobashsher AT, Abbosh AM. Compact 3-D slot-loaded folded dipole antenna with unidirectional radiation and low impulse distortion for head imaging applications. IEEE Trans Antenn Propag 2016; 64(7): 3245-50.
[http://dx.doi.org/10.1109/TAP.2016.2560909]
[7]
Alqadami ASM, Mobashsher AT. Wearable electromagnetic head imaging system using flexible wideband antenna array based on polymer technology for brain stroke diagnosis”. IEEE Trans Biomed Circuits Syst 2019; 13(1): 124-34.
[8]
Alqadami ASM, Trakic A, Stancombe AE, Mohammed B, Bialkowski K, Abbosh A. Flexible electromagnetic cap for head imaging. IEEE Trans Biomed Circuits Syst 2020; 14(5): 1097-107.
[http://dx.doi.org/10.1109/TBCAS.2020.3025341] [PMID: 32956066]
[9]
Zhang X, Chen Y, Tian M, Liu J, Liu H. A compact wide-band antipodal Vivaldi antenna design. Int J RF Microw Comput-Aided Eng 2018; 29(4): e21598.
[10]
Yesilyurt O, Turhan-Sayan G. Metasurface lens for ultra-wideband planar antenna. IEEE Trans Antenn Propag 2020; 68(2): 719-26.
[http://dx.doi.org/10.1109/TAP.2019.2940462]
[11]
Guo L, Yang H, Zhang Q, Deng M. A compact antipodal tapered slot antenna with artificial material lens and reflector for GPR applications. IEEE Access 2018; 6: 44244-51.
[http://dx.doi.org/10.1109/ACCESS.2018.2864618]
[12]
Ireland D, Bialkowski KS, Abbosh AM. Microwave imaging for brain stroke detection using born iterative method. IET Microw Antennas Propag 2013; 7(11): 909-15.
[http://dx.doi.org/10.1049/iet-map.2013.0054]
[13]
Fear EC, Li X, Hagness SC, Stuchly MA. Confocal microwave imaging for breast cancer detection: Localization of tumors in three dimensions. IEEE Trans Biomed Eng 2002; 49(8): 812-22.
[http://dx.doi.org/10.1109/TBME.2002.800759] [PMID: 12148820]
[14]
Mustafa S, Mohammed B, Abbosh A. Novel preprocessing techniques for accurate microwave imaging of human brain. IEEE Antennas Wirel Propag Lett 2013; 12: 460-3.
[http://dx.doi.org/10.1109/LAWP.2013.2255095]
[15]
Mohammed BJ, Bialkowski KS, Abbosh AM. Radar-based timedomain head imaging using database of effective dielectric constant. Electron Lett 2015; 51(20): 1574-6.
[http://dx.doi.org/10.1049/el.2015.1376]
[16]
Warren C, Giannopoulos A, Giannakis I. gprMax: Open source software to simulate electromagnetic wave propagation for ground penetrating radar. Comput Phys Commun 2016; 209: 163-70.
[http://dx.doi.org/10.1016/j.cpc.2016.08.020]
[17]
Guo J, Tong J, Zhao Q, Jiao J, Huo J, Ma C. An ultrawide band antipodal vivaldi antenna for airborne GPR application. IEEE Geosci Remote Sens Lett 2019; 16(10): 1560-4.
[http://dx.doi.org/10.1109/LGRS.2019.2905013]
[18]
Fhager A, Candefjord S, Elam M, Persson M. Microwave diagnostics ahead: Saving time and the lives of trauma and stroke patients. IEEE Microw Mag 2018; 19: 78-90.
[http://dx.doi.org/10.1109/MMM.2018.2801646]
[19]
Hopfer M, Planas R, Hamidipour A, Henriksson T, Semenov S. Electromagnetic tomography for detection, differentiation, and monitoring of brain stroke: A virtual data and human head phantom study. IEEE Antennas Propag Mag 2017; 59: 86-97.
[http://dx.doi.org/10.1109/MAP.2017.2732225]
[20]
Liu Z, Wu W, Gu X, Li S, Wang L, Zhang T. Application of combining YOLO models and 3D GPR images in road detection and maintenance. Remote Sens 2021; 13(6): 1081.
[http://dx.doi.org/10.3390/rs13061081]

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