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      Levels of detail analysis of microwave scattering from human head models for brain stroke detection

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          Abstract

          In this paper, we have presented a microwave scattering analysis from multiple human head models. This study incorporates different levels of detail in the human head models and its effect on microwave scattering phenomenon. Two levels of detail are taken into account; (i) Simplified ellipse shaped head model (ii) Anatomically realistic head model, implemented using 2-D geometry. In addition, heterogenic and frequency-dispersive behavior of the brain tissues has also been incorporated in our head models. It is identified during this study that the microwave scattering phenomenon changes significantly once the complexity of head model is increased by incorporating more details using magnetic resonance imaging database. It is also found out that the microwave scattering results match in both types of head model (i.e., geometrically simple and anatomically realistic), once the measurements are made in the structurally simplified regions. However, the results diverge considerably in the complex areas of brain due to the arbitrary shape interface of tissue layers in the anatomically realistic head model.

          After incorporating various levels of detail, the solution of subject microwave scattering problem and the measurement of transmitted and backscattered signals were obtained using finite element method. Mesh convergence analysis was also performed to achieve error free results with a minimum number of mesh elements and a lesser degree of freedom in the fast computational time. The results were promising and the E-Field values converged for both simple and complex geometrical models. However, the E-Field difference between both types of head model at the same reference point differentiated a lot in terms of magnitude. At complex location, a high difference value of 0.04236 V/m was measured compared to the simple location, where it turned out to be 0.00197 V/m. This study also contributes to provide a comparison analysis between the direct and iterative solvers so as to find out the solution of subject microwave scattering problem in a minimum computational time along with memory resources requirement.

          It is seen from this study that the microwave imaging may effectively be utilized for the detection, localization and differentiation of different types of brain stroke. The simulation results verified that the microwave imaging can be efficiently exploited to study the significant contrast between electric field values of the normal and abnormal brain tissues for the investigation of brain anomalies. In the end, a specific absorption rate analysis was carried out to compare the ionizing effects of microwave signals to different types of head model using a factor of safety for brain tissues. It is also suggested after careful study of various inversion methods in practice for microwave head imaging, that the contrast source inversion method may be more suitable and computationally efficient for such problems.

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          Computerized three-dimensional segmented human anatomy.

          Manual segmentation of 129 x-ray CT transverse slices of a living male human has been done and a computerized 3-dimensional volume array modeling all major internal structures of the body has been created. Each voxel of the volume contains a index number designating it as belonging to a given organ or internal structure. The original x-ray CT images were reconstructed in a 512 x 512 matrix with a resolution of 1 mm in the x,y plane. The z-axis resolution is 1 cm from neck to midthigh and 0.5 cm from neck to crown of the head. This volume array represents a high resolution model of the human anatomy and can serve as a voxel-based anthropomorphic phantom suitable for many computer-based modeling and simulation calculations.
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            Stroke epidemiology in the developing world.

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              4: Rehabilitation after traumatic brain injury.

              Traumatic brain injury (TBI) commonly affects younger people and causes life-long impairments in physical, cognitive, behavioural and social function. The cognitive, behavioural and personality deficits are usually more disabling than the residual physical deficits. Recovery from TBI can continue for at least 5 years after injury. Rehabilitation is effective using an interdisciplinary approach, and close liaison with the patient, family and carers. The focus is on issues such as retraining in activities of daily living, pain management, cognitive and behavioural therapies, and pharmacological management. The social burden of TBI is significant, and therefore family education and counselling, and support of patient and carers, is important. General practitioners play an important role in providing ongoing support in the community, monitoring for medical complications, behavioural and personality issues, social reintegration, carer coping skills and return-to-work issues.
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                Author and article information

                Contributors
                Journal
                PeerJ
                PeerJ
                PeerJ
                PeerJ
                PeerJ
                PeerJ Inc. (San Francisco, USA )
                2167-8359
                21 November 2017
                2017
                : 5
                : e4061
                Affiliations
                Research Center for Modeling and Simulation (RCMS), National University of Sciences and Technology (NUST) H-12 , Islamabad, Pakistan
                Article
                4061
                10.7717/peerj.4061
                5701549
                ab6b03c1-6344-44ba-9f81-c9b97de5a36c
                © 2017 Qureshi and Mustansar

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited.

                History
                : 8 June 2017
                : 28 October 2017
                Funding
                The authors received no funding for this work.
                Categories
                Bioengineering
                Biophysics
                Radiology and Medical Imaging
                Computational Science

                microwave imaging,finite element method,human brain stroke,forward problem,inverse problem,levels of detail

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