Results 1 
5 of
5
Iterative tomographic image reconstruction using Fourierbased forward and back projectors
 IEEE Trans. Med. Imag
, 2004
"... Fourierbased reprojection methods have the potential to reduce the computation time in iterative tomographic image reconstruction. Interpolation errors are a limitation of Fourierbased reprojection methods. We apply a minmax interpolation method for the nonuniform fast Fourier transform (NUFFT) t ..."
Abstract

Cited by 25 (4 self)
 Add to MetaCart
Fourierbased reprojection methods have the potential to reduce the computation time in iterative tomographic image reconstruction. Interpolation errors are a limitation of Fourierbased reprojection methods. We apply a minmax interpolation method for the nonuniform fast Fourier transform (NUFFT) to minimize the interpolation errors. Numerical results show that the minmax NUFFT approach provides substantially lower approximation errors in tomographic reprojection and backprojection than conventional interpolation methods.
A fast and accurate multilevel inversion of the radon transform
 SIAM J. Appl. Math
, 1999
"... Abstract. A number of imaging technologies reconstruct an image function from its Radon projection using the convolution backprojection method. The convolution is an O(N 2 log N) algorithm, where the image consists of N ×N pixels, while the backprojection is an O(N 3) algorithm, thus constituting th ..."
Abstract

Cited by 13 (2 self)
 Add to MetaCart
(Show Context)
Abstract. A number of imaging technologies reconstruct an image function from its Radon projection using the convolution backprojection method. The convolution is an O(N 2 log N) algorithm, where the image consists of N ×N pixels, while the backprojection is an O(N 3) algorithm, thus constituting the major computational burden of the convolution backprojection method. An O(N 2 log N) multilevel backprojection method is presented here. When implemented with a Fourierdomain postprocessing technique, also presented here, the resulting image quality is similar or superior to the image quality of the classical backprojection technique. Key words. Radon transform, inversion of the Radon transform, computed tomography, convolution backprojection, multilevel, Fourierdomain postprocessing AMS subject classifications. 92C55, 44A12, 65R10, 68U10 PII. S003613999732425X 1. Background. Reconstruction of a function of two or three variables from its Radon transform has proven vital in computed tomography (CT), nuclear magnetic resonance imaging, astronomy, geophysics, and a number of other fields [13]. One of the best known reconstruction algorithms is the convolution backprojection method (CB), which is widely used in commercial CT devices [13] (with rebinning for divergentbeam projections [18]). Recently, it has been applied to spotlightmode synthetic aperture radar image reconstruction [14, 23] in which the conventional method is the direct Fourier method (DF), i.e., Fourierdomain interpolation followed by twodimensional (2D) FFT [21]. Originally, CB was preferred to DF since the former provided better images [18, 20]. However, since the backprojection part of CB raises the computational complexity of the method to O(N 3), while DF’s complexity is O(N 2 log N), there has been
An O(N² log N) Multilevel Backprojection Method
"... A number of imaging technologies reconstruct an image function from its Radon projection using the convolution backprojection method. The convolution is an O(N² log N ) algorithm, where the image consists of N x N pixels, while the backprojection is an O(N³) algorithm, thus constituting the major c ..."
Abstract
 Add to MetaCart
A number of imaging technologies reconstruct an image function from its Radon projection using the convolution backprojection method. The convolution is an O(N² log N ) algorithm, where the image consists of N x N pixels, while the backprojection is an O(N³) algorithm, thus constituting the major computational burden of the convolution backprojection method. An O(N² log N ) multilevel backprojection method is presented here. When implemented with a Fourierdomain postprocessing technique, also presented here, the resulting image quality is similar to or superior than the image quality of the classical backprojection technique.
FOURIERBASED FORWARD AND BACKPROJECTORS IN ITERATIVE FANBEAM TOMOGRAPHIC IMAGE RECONSTRUCTION
"... Fourierbased forward and backprojection methods have the potential to reduce computation demands in iterative tomographic image reconstruction. Interpolation errors are a limitation of conventional Fourierbased projectors. Recently, the minmax optimized KaiserBessel interpolation within the n ..."
Abstract
 Add to MetaCart
(Show Context)
Fourierbased forward and backprojection methods have the potential to reduce computation demands in iterative tomographic image reconstruction. Interpolation errors are a limitation of conventional Fourierbased projectors. Recently, the minmax optimized KaiserBessel interpolation within the nonuniform Fast Fourier transform (NUFFT) approach has been applied in parallelbeam image reconstruction, whose results show lower approximation errors than conventional interpolation methods. However, the extension of minmax NUFFT approach to fanbeam data has not been investigated. We have extended the minmax NUFFT framework to the fanbeam tomography case, using the relationship between the fanbeam projections and corresponding projections in parallelbeam geometry. Our studies show that the fanbeam Fourierbased forward and backprojection methods can significantly reduce computation time while still providing comparable accuracy to their spacebased counterparts. 1.
NOISE PROPERTIES OF REGULARIZED IMAGE RECONSTRUCTION IN XRAY COMPUTED TOMOGRAPHY
, 2007
"... is the endofjourney harvest of my five and half years of hard work whereby I have been inspired and encouraged by many people. It is my greatest pleasure to express my deepest and sincerest gratitude for all of them. This thesis would not exist without my advisor, Professor Jeffrey A. Fessler. His ..."
Abstract
 Add to MetaCart
(Show Context)
is the endofjourney harvest of my five and half years of hard work whereby I have been inspired and encouraged by many people. It is my greatest pleasure to express my deepest and sincerest gratitude for all of them. This thesis would not exist without my advisor, Professor Jeffrey A. Fessler. His enlightening guidance, colossal support and sincere friendship helped me from day one and throughout my graduate study. I would also like to express my gratitude to Professor Neal H. Clinthorne, Professor Mitchell M. Goodsitt, Professor Alfred O. Hero, and Professor David C. Munson for their expertise and valuable feedbacks on this work. I give special thanks to Professor Anthony W. England for his understanding and assistance in my transition of research fields. I further present my gratefulness to the colleagues at University