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

• Published in: PeerJ (San Francisco, CA) CA), 2017-11, Vol.5, p.e4061-e4061, Article e4061
• Main Authors: Qureshi, Awais Munawar, Mustansar, Zartasha
• Format: Article
• Language: English
• Subjects: Analysis; Bioengineering; Biophysics; Brain research; Computational neuroscience; Computational Science; Diagnosis; Diagnostic imaging; Feasibility studies; Finite element method; Forward problem; Head; Human brain stroke; Inverse problem; Levels of detail; Localization; Magnetic resonance imaging; Medical imaging; Methods; Microwave imaging; Neuroimaging; NMR; Nuclear magnetic resonance; Radiology and Medical Imaging; Scattering (Physics); Stroke
• ISSN: 2167-8359; 2167-8359
• DOI: 10.7717/peerj.4061

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