A reconstruction algorithm using singular value decomposition of a discrete representation of the exponential radon transform using natural pixels

Publisher Website
Google Scholar
Abstract
An algorithm to correct for constant attenuation in SPECT is derived from the singular value decomposition (SVD) of a discrete representation of the exponential Radon transform using natural pixels. The algorithm is based on the assumption that a continuous image can be obtained by backprojecting the discrete array q, which is the least squares solution to Mq=p, where p is the array of discrete measurements, and the matrix M represents the composite operator of the backprojection operator A/sub /spl mu//* followed by the projection operator A/sub /spl mu//. A singular value decomposition of M is used to solve the equation Mq=p, and the final image is obtained by sampling the backprojection of the solution q at a discrete array of points. Analytical expressions are given to calculate the matrix elements of M that are integrals of exponential factors over the overlapped area of two projection strip functions (natural pixels). A spectral analysis of the exponential Radon transform is compared with that of the Radon transform. The condition number of the spectrum increases with increased attenuation coefficient, which correlates with the increase in statistical error propagation seen in clinical images obtained with low-energy radionuclides. Computer simulations using 32 projections sampled over 360 degrees show an improvement in the SVD reconstruction over the convolution backprojection reconstruction, especially when the projection data is corrupted with noise.