A Novel GUI-Based Image Reconstruction Algorithm of EIT Imaging Technique

2. Background

Many non-linear and linear algorithms are used for reconstruction of imaging in the medical and industrial field (Mengxing et al., 1998), such as regularization methods, sensitivity matrix method, equipotential back projection, and Newton-Rapson method, etc. The Newton-Rapson method is applicable for non-linear applications. The computation time under this method is higher as compared to linear techniques due to involvement of higher order equation magnitude (Borsic & Bayford, 2010). Above shown all technique, as provides realistic solutions and require simplifying hypotheses about the problem. All the techniques discussed earlier are having capacity to provide real time solution for the problem by simplifying hypothesis. Finite Element Method (FEM) converts continuous system solution into approximated discrete system consists of meshes, elements and nodes in finite number (Kilic et al., 1998). Here, we use a finite element model to simulate the impedance distribution field in image tomography (Seok, 2014). The tomography study aims to establish the distributed conductivity environment with the help of electrical conductivity distribution function using data measured over the boundary within the body (Soni, 2006). From the previous research is found that the finite element method is most suitable for this type of problems of the inhomogeneous field with arbitrary geometry. A finite element model has been employed in the article to express the electrical impedance distribution for the object or body field (Olmos, 2012).