Variance prediction in SPECT reconstruction based on the Fisher information using a novel angular blurring algorithm for computation of the system matrix
In this paper we propose a Gaussian decomposition approach to compute the SPECT imaging system matrix. The flexibility of our method allows the implementation of a wide range of imaging systems. With the system matrix, we predict the variance in reconstructed images using the Fisher information matrix and local block circulant approximation. We present results of noise prediction for 3 multi-pinhole systems and 3 multi-slit slit-slat systems, each of them being designed to be inserted in an MRI system. Results show that for a particular phantom 2×2 multi-pinhole and 2 slits slit-slat systems achieve lowest variance.
This study aims to analyse the spatial characteristics and to draw the declining areas from the whole area of Chung-Cheong Province. For this purpose, the temporal and spatial conditions by the urban decline diagnosis indexes are utilized. Additionally, the spatial autocorrelation method was applied for extraction of those areas. The spatial autocorrelation method is one of the methods on exploring spatial characteristics and considering the spatial factors. We also adopted the concepts of economics and then discovered the characteristics of deprivation areas. In applying this method, the positively valued areas were classified as the complementary areas, and the negatively valued areas as the substitutional areas. The findings show the declining areas and the growing areas caused by the growth of periphery. This study supports the regeneration plan of Chung-Cheong Province in extracting depressed or activated areas and explaining the characteristics of those areas.