Title :
Tomography: the Cormack algorithm revisited
Author :
Zahrt, John D. ; Faber, V. ; Wing, G. Milton
Author_Institution :
Los Alamos Nat. Lab., NM, USA
Abstract :
Summary form only given. The Cormack algorithm for doing tomography is easily extended from parallel geometry to fan geometry. After a Fourier transform of the data (in rotation angle space) one is required to solve a truncated system before back Fourier transforming to object space. This is carried out by doing a Galerkin discretization and converting the system to a system of matrix equations, which are solved by singular value decomposition (SVD). All of the SVD work on all N+1 kernels, can be done once and stored. Some reconstructions derived from very noisy data have been obtained.<>
Keywords :
computerised tomography; image reconstruction; Cormack algorithm; Galerkin discretization; back Fourier transformation; fan geometry; kernels; matrix equations system; medical diagnostic imaging; noisy data; object space; parallel geometry; rotation angle space; singular value decomposition; Chebyshev approximation; Equations; Geometry; Kernel; Laboratories; Matrix converters; Matrix decomposition; Polynomials; Singular value decomposition; Tomography;
Conference_Titel :
Nuclear Science Symposium and Medical Imaging Conference, 1991., Conference Record of the 1991 IEEE
Conference_Location :
Santa Fe, NM, USA
Print_ISBN :
0-7803-0513-2
DOI :
10.1109/NSSMIC.1991.259285
