A METHOD FOR COMPARATIVE-EVALUATION OF EIT ALGORITHMS USING A STANDARD DATA SET

The point spread function (PSF) is the most widely used tool for quant ifying the spatial resolution of imaging systems. However, prerequisit es for the proper use of this tool are linearity and space invariance. Because EIT is non-linear it is only possible to compare different re construction algorithms using a standard data set. In this study, the FEM is used to generate simulation data, which are used to investigate the non-linear behaviour of EIT, the space dependence of its PSF and its capability of resolving nearby objects. It is found that for the c ase of iterative backprojection (IterB), the full width half maximum ( FWHM) values of single-object perturbations for central, intermediate and peripheral high-contrast objects are 27%, 18% and 14% of the imagi ng region diameter respectively. For the method based on singular valu e decomposition of the Geselowitz lead sensitivity matrix (GS-SVD), th e FWHM is not space dependent and is 12% of the imaging region diamete r. Conclusions obtained using single-object PSF studies must also be c hecked with double-object or more complex perturbations because EIT is non-linear. For example, the GS-SVD method fails to detect two widely separated objects unless the truncation level of SVD is carefully adj usted. With more truncation, however, the resolution of the method is worsened. Based on these and similar observations a set of simulation data, which is proposed for comparative evaluation of different EIT al gorithms, is specified and explained in the conclusion section.