Title :
Tomographic image sequence reconstruction by edge-preserving interslice MAP methods
Author :
Ding, Wei ; Liu, Bede
Author_Institution :
Dept. of Electr. Eng., Princeton Univ., NJ, USA
fDate :
1/1/1996 12:00:00 AM
Abstract :
We consider a new problem in tomographic imaging. In a sequence of transverse images, adjacent slices often look similar to each other. We investigate the possibility of using this correlation to help reconstruct the sequence with 2-D in-plane data. The problem is formulated as a maximum a posteriori (MAP) estimation problem, using an edge-preserving Markov random field prior model. Both Gaussian and Poisson data are considered. Some improvements over the single-slice MAP reconstructions are observed
Keywords :
Markov processes; computerised tomography; emission tomography; image reconstruction; image sequences; maximum likelihood estimation; medical image processing; nondestructive testing; random processes; 2D in-plane data; Gaussian data; Poisson data; brain images; correlation; edge-preserving Markov random field prior model; edge-preserving interslice MAP methods; medical diagnostics; nondestructive materials testing; single-slice MAP reconstructions; tomographic image sequence reconstruction; transverse images; Detectors; Event detection; Image reconstruction; Image sequences; Iterative algorithms; Markov random fields; Materials testing; Medical diagnosis; Tomography; X-ray imaging;
Journal_Title :
Image Processing, IEEE Transactions on
