Title :
Approximate variance images for penalized-likelihood image reconstruction
Author :
Fessler, Jeffrey A.
Author_Institution :
Michigan Univ., Ann Arbor, MI, USA
Abstract :
The authors present a fairly simple procedure for computing new approximations for the pixel variances in images reconstructed by penalized-likelihood methods. The method enables the display of variance images, which can provide an indication of uncertainty that may be helpful in medical diagnosis and in evaluation of image reconstruction algorithms. Simulations of positron emission tomography (PET) scans illustrate the accuracy of the proposed variance approximations in nonzero image pixels
Keywords :
image reconstruction; medical image processing; positron emission tomography; PET scans simulation; approximate variance images; image reconstruction algorithms evaluation; medical diagnosis; nonzero image pixels; nuclear medicine; penalized-likelihood image reconstruction; pixel variances approximations computation; variance images display; Biomedical imaging; Computational modeling; Covariance matrix; Displays; Gaussian noise; Image reconstruction; Medical diagnostic imaging; Physics computing; Pixel; Tomography;
Conference_Titel :
Nuclear Science Symposium, 1997. IEEE
Conference_Location :
Albuquerque, NM
Print_ISBN :
0-7803-4258-5
DOI :
10.1109/NSSMIC.1997.670467
