Implementation Of Non-linear Filters For Iterative Penalized Maximum Likelihood Image Reconstruction

Six low-pass linear filters applied in frequency space were implemented for iterative penalized maximum-likelihood (ML) single photon emission computed tomography (SPECT) image reconstruction. The filters implemented were the Shepp-Logan filter, the Butterworth filter, the Gaussian filter, the Hann filter, the Parzen filter, and the Lagrange filter. The low-pass filtering was applied in frequency space to projection data for the initial estimate and to the difference of projection data and reprojected data for higher-order approximations. The projection data were acquired experimentally from a chest phantom consisting of nonuniform attenuating media. All the filters could effectively remove the noise and edge artifacts associated with the ML approach if the frequency cutoff was properly chosen. The improved performance of the Parzen and Lagrange filters relative to the others was observed. The best image. by viewing its profiles in terms of noise-smoothing, edge-sharpening, and contrast, was obtained by Parzen filter. However, the Lagrange filter has the potential to consider the characteristics of the detector response function. >

[1]  C. K. Yuen,et al.  Digital Filters , 1979, IEEE Transactions on Systems, Man, and Cybernetics.

[2]  R. A. Leibler,et al.  On Information and Sufficiency , 1951 .

[3]  C E Metz,et al.  Quantitative effects of stationary linear image processing on noise and resolution of structure in radionuclide images. , 1974, Journal of nuclear medicine : official publication, Society of Nuclear Medicine.

[4]  Jong-Sen Lee,et al.  Digital image smoothing and the sigma filter , 1983, Comput. Vis. Graph. Image Process..

[5]  E. Tanaka,et al.  A Filtered Iterative Reconstruction Algorithm for Positron Emission Tomography , 1988 .

[6]  Thomas F. Budinger,et al.  The Use of Filtering Methods to Compensate for Constant Attenuation in Single-Photon Emission Computed Tomography , 1981 .

[7]  Thomas S. Huang,et al.  A fast two-dimensional median filtering algorithm , 1979 .

[8]  T. M. Peters.  Algorithms for Fast Back- and Re-Projection in Computed Tomography , 1981 .

[9]  David L. Phillips,et al.  A Technique for the Numerical Solution of Certain Integral Equations of the First Kind , 1962, JACM.

[10]  Z Liang,et al.  A spatial interaction model for statistical image processing. , 1991, Progress in clinical and biological research.

[11]  C. Metz,et al.  The exponential Radon transform , 1980 .

[12]  H. Hart,et al.  Bayesian Image Processing in Two Dimensions , 1987, IEEE Transactions on Medical Imaging.

[13]  David C. Wang,et al.  Gradient inverse weighted smoothing scheme and the evaluation of its performance , 1981 .

[14]  R. Jaszczak,et al.  On Bayesian image reconstruction from projections: uniform and nonuniform a priori source information. , 1989, IEEE transactions on medical imaging.

[15]  William K. Pratt,et al.  Generalized Wiener Filtering Computation Techniques , 1972, IEEE Transactions on Computers.

[16]  L. Shepp,et al.  Maximum Likelihood Reconstruction for Emission Tomography , 1983, IEEE Transactions on Medical Imaging.

[17]  B. F. Logan,et al.  The Fourier reconstruction of a head section , 1974 .

[18]  Donald Geman,et al.  Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images , 1984, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[19]  K. Lange,et al.  EM reconstruction algorithms for emission and transmission tomography. , 1984, Journal of computer assisted tomography.

[20]  D R Gilland,et al.  Quantitative SPECT reconstruction of iodine-123 data. , 1991, Journal of nuclear medicine : official publication, Society of Nuclear Medicine.

[21]  Ronald J. Jaszczak,et al.  Reprojection and backprojection in SPECT image reconstruction , 1989, Proceedings. IEEE Energy and Information Technologies in the Southeast'.

[22]  E. Parzen.  Mathematical Considerations in the Estimation of Spectra , 1961 .

[23]  N. Pelc,et al.  An attenuated projector-backprojector for iterative SPECT reconstruction. , 1985, Physics in medicine and biology.

[24]  Roland T. Chin,et al.  Quantitative evaluation of some edge-preserving noise-smoothing techniques , 1983, Comput. Vis. Graph. Image Process..

[25]  Eiichi Tanaka.  A Fast Reconstruction Algorthm for Stationary Positron Emission Tomography Based on a Modified EM Algorithm , 1987, IEEE Transactions on Medical Imaging.

[26]  Stuart Geman,et al.  Statistical methods for tomographic image reconstruction , 1987 .

[27]  E. Tanaka,et al.  Intelligent Iterative Image Reconstruction With Automatic Noise Artifact Suppression , 1990, 1990 IEEE Nuclear Science Symposium Conference Record.

[28]  L. J. Thomas,et al.  Noise and Edge Artifacts in Maximum-Likelihood Reconstructions for Emission Tomography , 1987, IEEE Transactions on Medical Imaging.

[29]  P W Doherty,et al.  Digital restoration of indium-111 and iodine-123 SPECT images with optimized Metz filters. , 1986, Journal of nuclear medicine : official publication, Society of Nuclear Medicine.