Novel Preprocessing Techniques for Accurate Microwave Imaging of Human Brain

Mustafa, Samah; Mohammed, Beadaa; Abbosh, Amin

doi:10.1109/lawp.2013.2255095

Cited by 142 publications

(105 citation statements)

References 12 publications

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“…Only the subspace containing useful information is selected, and artifacts are discarded. Head symmetry [15]: The artifacts are removed by subtracting the backscattered signals at antenna that face each other in the array with respect to the head midline, i.e., the central line that divides the head into left and right hemisphere.…”

Section: Preprocessing Phasementioning

confidence: 99%

“…Moreover, a novel algorithm based on PLSR (partial least square regression) has been proposed and compared with the Wiener filtering. In [15], two novel algorithms for stroke detection have been proposed and their performance assessed. They are based on the symmetry with respect to the head midline that divides the head in left and right hemisphere.…”

Section: Introductionmentioning

confidence: 99%

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PCA-based artifact removal algorithm for stroke detection using UWB radar imaging

Ricci

Domenico

Cianca

et al. 2016

Med Biol Eng Comput

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Section: Preprocessing Phasementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

PCA-based artifact removal algorithm for stroke detection using UWB radar imaging

Ricci

Domenico

Cianca

et al. 2016

Med Biol Eng Comput

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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%

“…In 2013, a wideband microwave system for head imaging, utilizing a semielliptical array of 16 corrugated tapered slot antennas (1-4 GHz) installed on an adjustable platform, was presented by Mohammed, et al [8], and Abbosh [30]. A preprocessing algorithm was applied to extract the target response from the strong background reflections [31]. A post-processing algorithm based on confocal delay-and-sum approach and Fermat's principle was developed to construct a high-resolution image of the phantom.…”

Section: Introductionmentioning

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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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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“…The interest in microwave brain stroke localization has drawn people's interest because of its low cost and portability [1]. Several research groups have reported microwave imaging systems or devices [2][3][4][5][6]. To validate the effectiveness of microwave imaging methods, a phantom imitating human head in electrical and anatomical aspects is required [6][7][8].…”

Section: Introductionmentioning

confidence: 99%

Realistic Head Phantom for Evaluation of Brain Stroke Localization Methods Using 3D Printer

Lee¹,

Bang²,

Choi³

2016

Journal of electromagnetic engineering and science

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In this paper, a brain phantom for evaluating brain stroke localization is proposed. To evaluate brain stroke localization, a phantom imitating three-dimensional (3D) simulation environment is needed. Mold for the proposed phantom was printed by a 3D printer and the interior of the phantom consists of 5 different brain tissue materials. Each of the brain tissue materials has the conductivity and permittivity similar to those of the International Commission on Non-Ionizing Radiation Protection (ICNIRP) standards for a frequency band from 0.5 to 2 GHz.Key Words: Brain, Phantom, Stroke Localization, 3D Printer. Manuscript received August 12, 2016 ; Revised October 12, 2016 ; Accepted October 17, 2016. (ID No. 20160812-026J) Department of Electronics and Computer Engineering, Hanyang University, Seoul, Korea * Corresponding Author: Jaehoon Choi (e-mail: choijh@hanyang.ac.kr) This is an Open-Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. ⓒ Copyright The Korean Institute of Electromagnetic Engineering and Science. All Rights Reserved. LEE et al.: REALISTIC HEAD PHANTOM FOR EVALUATION OF BRAIN STROKE LOCALIZATION METHODS USING 3D PRINTER 255Dimensions for the molds of a phantom (height, 265 mm; sagittal width, 260 mm; coronal width, 197 mm; and thickness of mold, 8-12 mm) are the same as brain CAD data provided by ANSYS HFSS (ver. 14). However, the CAD data could not be applied directly to the phantom molds since the data had holes and overlapping parts. The ANSYS CAD data was modified to enclose each brain tissue and to eliminate overlapped parts. In addition, the oval and nasal cavities were eliminated. The brain model was printed as molds by MakerBot 3D printer whose resolution was 0.1 mm [12]. Fig. 1(a) shows the 3D printer. Even though the real brain consists of a lot of tissues, CAD data of the molds, and (c) photo of the molds. the brain was subdivided into 4 major tissues (spinal cord, cerebellum, white matter, and cerebrospinal fluid) in our head phantom model. The printed molds consist of outer parts and inner molds, including white matter, cerebellum, and spinal cord, as shown in Fig. 1(b) and (c). The outer molds were used as the outer shell of the brain phantom, while the inner molds were used to separate and shape the brain tissue materials, and were extracted after the tissues solidified. The inner molds were used only for shaping and locating the brain tissue materials. Spinal cord, cerebellum, and white matter among the subdivided 4 major brain tissues were embedded with supporters to main the proper locations. The filament used for making the molds is polylactic acid (PLA) and its relative permittivity is about 2.0. Recipes for the Blood and Brain Tissue MaterialsRecipes for the 4 brain tissue materials and blood material were developed such that the ...

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Novel Preprocessing Techniques for Accurate Microwave Imaging of Human Brain

Cited by 142 publications

References 12 publications

PCA-based artifact removal algorithm for stroke detection using UWB radar imaging

PCA-based artifact removal algorithm for stroke detection using UWB radar imaging

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

Realistic Head Phantom for Evaluation of Brain Stroke Localization Methods Using 3D Printer

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