Microwave imaging for brain stroke detection using Born iterative method

Ireland, David; Bialkowski, Konstanty; Abbosh, Amin

doi:10.1049/iet-map.2013.0054

Cited by 141 publications

(80 citation statements)

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“…An appropriate image reconstruction method is selected based on the particular application. The most frequently used non-linear inversion methods include; Contrast Source Inversion (CSI), GaussNewton Inversion (GNI), Confocal Delay-and-Sum Algorithm and Born Iterative Method (BIM) [8,17,20,28,31,38].…”

Section: Inverse Problem Solutionmentioning

confidence: 99%

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An Investigation Into Electromagnetic Based Impedance Tomography Using Realistic Human Head Model

Munawar

Mustansar

Nadeem

et al. 2016

Int J Pharm Pharm Sci

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College of Electrical and Mechanical Engineering, National University of Sciences and Technology, Islamabad, Pakistan Email: awaismunawar.phd06@rcms.nust.edu.pkThe objective of this research is to investigate the feasibility of Electromagnetic based Impedance Tomography (EMIT) for brain stroke detection, localization and classification. Electromagnetic based Impedance Tomography employing microwave imaging technique is an emerging brain stroke diagnostic modality. It relies on the significant contrast between dielectric properties of the normal and abnormal brain tissues. To study the interaction between micro-wave signals and head tissues, the simulations are performed using a geometrically simple 3-D ellipsoid head model with emulated stroke. Finite Element numerical technique is adopted to find the solution of Maxwell's equations to measure the transmitted and backscattered signals in forward problem. Contrast Source Inversion technique is proposed to solve the inverse scattering problem and reconstruct brain images based on calculated dielectric profiles. Detailed analysis is performed to determine the safety limits of transmitted signals to minimize ionizing effects while ensuring maximum penetration. The simulations verify the inhomogeneous and frequency-dispersive behavior of brain tissue's dielectric properties. The solution of the forward problem demonstrates the microwave signals scattering by the multilayer structure of the head model, duly validated by analytical results. The scattering phenomena can be fully capitalized by image reconstruction algorithm to obtain brain images and detect stroke presence. The initial results obtained in this research and prior work indicates that EMIT-based head imaging system has a potential for rapid stroke detection, classification, and continuous brain monitoring and offers a comparatively cost-effective solution.

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Section: Inverse Problem Solutionmentioning

confidence: 99%

“…The model has been effectively utilized in several studies conducted by different researchers [7,[17][18][19][20][21].…”

mentioning

confidence: 99%

An Investigation Into Electromagnetic Based Impedance Tomography Using Realistic Human Head Model

Munawar

Mustansar

Nadeem

et al. 2016

Int J Pharm Pharm Sci

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“…On the other hand, wideband microwave imaging method is based on radar techniques which directly looks for the location of the significant scatterers (hemorrhage, in this scenario) utilizing the scattered signals across a wide span of microwave frequencies. Wideband microwave imaging is well preferred over microwave tomography in head imaging system due to its advantages in such ill-conditioned non-linear problem inside heterogeneous human head, where tomography approach becomes very complex and takes longer time to reconstruct a map of head interior [14,15].…”

Section: Wideband Microwave Imaging -Advantages and Applicationsmentioning

confidence: 99%

“…Most of the reported head imaging systems utilize frequencies between 0.5-4 GHz in narrowband or wideband manner, as a compromise between the image resolution and signal penetration [14,15,[38][39][40][41][42][43]. The size of the antenna is the major design concern at these low frequencies, especially when wideband is demanded.…”

Section: Existing Microwave-based Head Imaging Systemsmentioning

confidence: 99%

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Wideband microwave imaging system for brain injury diagnosis

Mobashsher¹

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Brain injury is a major cause of disability and mortality worldwide. This medical emergency occurs when the brain is damaged as a result of various traumatic and non-traumatic incidences including accidents, strokes, drug abuses, tumours, infections and various diseases. As the devastating disorder of brain injury deteriorates rapidly, fast diagnosis and management is critically important for the treatment and recovery of the affected patient. Therefore, on-the-spot accurate detection by means of head imaging is the governing factor of the timely medication to ensure complete recovery of the injured patient. Although some existing imaging technologies, like CT and MRI, are capable for brain injury diagnosis, they are time-consuming, expensive, bulky and mostly stationary. Thus they cannot be carried by first response paramedic teams for the diagnosis purpose or be used for monitoring the patient to observe concurrent brain injury over periods of time without moving the patient. A compact and mobile technology that can be applied to monitor the patient continuously in real time, either at the bedside or in emergency room, would be a significant advantage comparing to the existing imaging techniques. This thesis aims to develop wideband microwave imaging systems for brain injury diagnosis and in doing so makes seven main contributions to the field of microwave imaging systems.As the efficacy of the microwave imaging systems relies on the sensing antennas, emphasize is given in the developments of compact, wideband antennas with directional radiation patterns for low microwave frequencies, which is the first contribution of this thesis. Three-dimensional (3D) antennas are proposed relying on multiple folding and slot-loading techniques. Nevertheless, a novel generalized miniaturization technique is proposed for compact antennas. The antennas are found to be efficient in both near-and far-fields for both frequency-and time-domain characterizations.The second contribution is the development of artificial human head phantom with realistic heterogeneous tissue distributions and actual wideband frequency-dispersive dielectric properties.The phantom is fabricated from artificial tissue emulating materials which are contained and structured by using 3D printed structures and castes. This realistic 3D human head phantom significantly improves the reliability of the experimental validation process of wideband microwave imaging compared to the reported validations with existing simple and stylized head phantoms.The contribution third contribution is the performance comparison of directional and omni-directional antennas for wideband microwave head imaging systems. A novel near-field time-domain characterization technique is proposed that enables the comparative analysis of antennas for nearfield applications. Application of this technique demonstrates that for microwave imaging systems directional antennas are more effective than omni-directional antennas. In terms of imaging performance, it is observed that directio...

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Stroke localization and classification using microwave tomography with k‐means clustering and support vector machine

Abbosh

2018

Bioelectromagnetics

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For any chance for stroke patients to survive, the stroke type should be classified to enable giving medication within a few hours of the onset of symptoms. In this paper, a microwave-based stroke localization and classification framework is proposed. It is based on microwave tomography, k-means clustering, and a support vector machine (SVM) method. The dielectric profile of the brain is first calculated using the Born iterative method, whereas the amplitude of the dielectric profile is then taken as the input to k-means clustering. The cluster is selected as the feature vector for constructing and testing the SVM. A database of MRI-derived realistic head phantoms at different signal-to-noise ratios is used in the classification procedure. The performance of the proposed framework is evaluated using the receiver operating characteristic (ROC) curve. The results based on a two-dimensional framework show that 88% classification accuracy, with a sensitivity of 91% and a specificity of 87%, can be achieved. Bioelectromagnetics. 39:312-324, 2018. © 2018 Wiley Periodicals, Inc.

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Microwave imaging for brain stroke detection using Born iterative method

Cited by 141 publications

References 14 publications

An Investigation Into Electromagnetic Based Impedance Tomography Using Realistic Human Head Model

An Investigation Into Electromagnetic Based Impedance Tomography Using Realistic Human Head Model

Wideband microwave imaging system for brain injury diagnosis

Stroke localization and classification using microwave tomography with k‐means clustering and support vector machine

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