Priyadarshini N, Rajkumar E R
Annu Int Conf IEEE Eng Med Biol Soc. 2013;2013:2404-7. doi: 10.1109/EMBC.2013.6610023.
Stroke has become one of the leading causes of mortality worldwide and about 800 in every 100,000 people suffer from stroke each year. The occurrence of stroke is ranked third among the causes of acute death and first among the causes for neurological dysfunction. Currently, Neurological examinations followed by medical imaging with CT, MRI or Angiography are used to provide better identification of the location and the type of the stroke, however they are neither fast, cost-effective nor portable. Microwave technology has emerged to complement these modalities to diagnose stroke as it is sensitive to the differences between the distinct dielectric properties of the brain tissues and blood. This paper investigates the possibility of diagnosing the type of stroke using Finite Element Analysis (FEA). The object of interest is a simulated head phantom with stroke, created with its specifying material characteristics like electrical conductivity and relative permittivity. The phantom is then placed in an electromagnetic field generated by a dipole antenna radiating at 1 GHz. The FEM forward model solver computes the scattered electromagnetic field by finding the solution for the Maxwell's wave equation in the head volume. Subsequently the inverse scattering problem is solved using the Contrast Source Inversion (CSI) method to reconstruct the dielectric profile of the head phantom.
中风已成为全球主要死因之一,每年每10万人中约有800人罹患中风。中风的发生率在急性死亡原因中位列第三,在神经功能障碍原因中位居第一。目前,通过神经学检查,随后借助CT、MRI或血管造影等医学成像手段,以更好地识别中风的位置和类型,然而这些方法既不快速、性价比不高,也不便于携带。微波技术应运而生,以补充这些诊断中风的方式,因为它对脑组织和血液不同介电特性之间的差异敏感。本文研究了使用有限元分析(FEA)诊断中风类型的可能性。研究对象是一个带有中风的模拟头部模型,根据其特定的材料特性(如电导率和相对介电常数)创建。然后将该模型置于由辐射频率为1 GHz的偶极天线产生的电磁场中。有限元正向模型求解器通过求解头部区域内麦克斯韦波动方程来计算散射电磁场。随后,使用对比源反演(CSI)方法解决反散射问题,以重建头部模型的介电剖面。