Title :
Resolution and noise properties of MAP reconstruction for fully 3-D PET
Author :
Qi, Jinyi ; Leahy, Richard M.
Author_Institution :
Signal & Image Process. Inst., Univ. of Southern California, Los Angeles, CA, USA
fDate :
5/1/2000 12:00:00 AM
Abstract :
Derives approximate analytical expressions for the local impulse response and covariance of images reconstructed from fully three-dimensional (3-D) positron emission tomography (PET) data using maximum a posteriori (MAP) estimation. These expressions explicitly account for the spatially variant detector response and sensitivity of a 3-D tomograph. The resulting spatially variant impulse response and covariance are computed using 3-D Fourier transforms. A truncated Gaussian distribution is used to account for the effect on the variance of the nonnegativity constraint used in MAP reconstruction. Using Monte Carlo simulations and phantom data from the microPET small animal scanner, the authors show that the approximations provide reasonably accurate estimates of contrast recovery and covariance of MAP reconstruction for priors with quadratic energy functions. They also describe how these analytical results can be used to achieve near-uniform contrast recovery throughout the reconstructed volume.
Keywords :
Fourier transforms; Gaussian distribution; Monte Carlo methods; image reconstruction; image resolution; medical image processing; noise; positron emission tomography; 3-D Fourier transforms; MAP reconstruction; Monte Carlo simulations; contrast recovery; covariance; fully 3-D PET; maximum a posteriori estimation; microPET small animal scanner; noise properties; nonnegativity constraint; phantom data; reconstructed volume; resolution propertiess; spatially variant detector response; Detectors; Energy resolution; Fourier transforms; Image analysis; Image reconstruction; Image resolution; Lesions; Positron emission tomography; Smoothing methods; Spatial resolution; Algorithms; Analysis of Variance; Animals; Brain; Haplorhini; Humans; Image Processing, Computer-Assisted; Models, Theoretical; Monte Carlo Method; Normal Distribution; Phantoms, Imaging; Poisson Distribution; Tomography, Emission-Computed;
Journal_Title :
Medical Imaging, IEEE Transactions on