DocumentCode :
438642
Title :
Comparison of statistical reconstructions with isotropic and anisotropic resolution
Author :
Qi, Jinyi
Author_Institution :
Dept. of Biomed. Eng., California Univ., Davis, CA, USA
Volume :
6
fYear :
2004
fDate :
16-22 Oct. 2004
Firstpage :
3624
Abstract :
Statistical reconstruction methods based on the penalized maximum likelihood (or maximum a posteriori) principle have gained increasing attention in emission tomography. Fessler and Rogers have shown that the penalized maximum likelihood reconstruction with a conventional quadratic penalty results in anisotropic point spread functions (PSFs). Several approaches have been developed to design modified penalty functions to achieve isotropic PSFs. While an image with an isotropic PSF may be useful in some situations, its performance on clinical detection and quantitation tasks is unknown. In this paper, we compare the task performances using computer simulations. The lesion detectability is measured by a channelized Hotelling observer. The quantitation is evaluated by the bias and variance. The results show that reconstructions with an isotropic PSF may not be suitable for lesion detection and quantitation.
Keywords :
digital simulation; emission tomography; image reconstruction; maximum likelihood estimation; medical image processing; transfer functions; anisotropic point spread function; channelized Hotelling observer; computer simulation; emission tomography; lesion detection; maximum likelihood principle; statistical reconstruction method; Anisotropic magnetoresistance; Biomedical imaging; Computer simulation; Image reconstruction; Lesions; Maximum likelihood detection; Maximum likelihood estimation; Positron emission tomography; Reconstruction algorithms; Statistical analysis;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Nuclear Science Symposium Conference Record, 2004 IEEE
ISSN :
1082-3654
Print_ISBN :
0-7803-8700-7
Electronic_ISBN :
1082-3654
Type :
conf
DOI :
10.1109/NSSMIC.2004.1466668
Filename :
1466668
Link To Document :
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