Title :
Evaluation of maximum-likelihood based attenuation correction in positron emission tomography
Author :
Nuyts, J. ; Dupont, P. ; Stroobants, S. ; Maes, A. ; Mortelmans, L. ; Suetens, P.
Author_Institution :
Dept. of Nucl Med., Katholieke Univ., Leuven, Belgium
fDate :
8/1/1999 12:00:00 AM
Abstract :
In positron emission tomography, transmission scans are used to correct the acquired data for the effect of photon attenuation. The noise present in the transmission measurement often has a significant effect on the signal to noise ratio of the final attenuation corrected image of the tracer distribution. This study evaluates the effect of different attenuation correction strategies on the performance of human observers in a tumor detection task. The four strategies considered are: no attenuation correction, multiplication with the count ratio of blank and transmission sinograms, reprojection of a maximum-likelihood reconstruction, and reprojection of a maximum-a-posteriori reconstruction of the transmission sinogram. Performance in tumor detection was quantified as the contrast at which the number of errors increased beyond 20%. No statistically significant difference was found between classical attenuation correction and maximum-likelihood based correction. With maximum-a-posteriori based attenuation correction performance was significantly better than with the other methods
Keywords :
image reconstruction; maximum likelihood estimation; medical image processing; observers; positron emission tomography; attenuation corrected image; attenuation correction strategies; blank sinograms; convolution; count ratio; human observers performance; maximum-a-posteriori reconstruction; maximum-likelihood based attenuation correction; maximum-likelihood reconstruction; multiplication; noise model; photon attenuation effect; positron emission tomography; reprojection; signal to noise ratio; tracer distribution; transmission scans; transmission sinograms; tumor detection task; Attenuation; Image reconstruction; Kernel; Maximum likelihood detection; Neoplasms; Particle measurements; Pixel; Positron emission tomography; Signal to noise ratio; Smoothing methods;
Journal_Title :
Nuclear Science, IEEE Transactions on
