ASSESSMENT OF SCATTER COMPONENTS IN HIGH-RESOLUTION PET - CORRECTION BY NONSTATIONARY CONVOLUTION SUBTRACTION

Citation
M. Bentourkia et al., ASSESSMENT OF SCATTER COMPONENTS IN HIGH-RESOLUTION PET - CORRECTION BY NONSTATIONARY CONVOLUTION SUBTRACTION, The Journal of nuclear medicine, 36(1), 1995, pp. 121-130
Citations number
22
Categorie Soggetti
Radiology,Nuclear Medicine & Medical Imaging
ISSN journal
01615505
Volume
36
Issue
1
Year of publication
1995
Pages
121 - 130
Database
ISI
SICI code
0161-5505(1995)36:1<121:AOSCIH>2.0.ZU;2-X
Abstract
This paper describes a new approach to determine individual scatter ke rnels and to use them for scatter correction by integral transformatio n of the projections. Methods: Individual scatter components are fitte d on the projections of a line source by monoexponentials. The positio n-dependent scatter parameters of each scatter component are then used to design non-stationary scatter correction kernels for each point in the projection. These kernels are used in a convolution-subtraction m ethod which consecutively removes object, collimator and detector scat ter from projections. This method is based on a model which assumes th at image degradation results exclusively from Compton interactions of annihilation photons, thus neglecting further Compton interactions of object scatters with collimator and detector. Results: Subtraction of the object scatter component improved contrast typical of what is obta ined with standard convolution-subtraction methods. The collimator sca tter component is so weak that it can be safely combined with object s catter for correction. Subtraction of detector scatter from images did not improve contrast because statistical accuracy is degraded by remo ving counts from hot regions while cold regions (background) remain un changed. Conclusion: Subtraction of object and collimator scatter impr oves contrast only. The slight gain in image sharpness resulting from the subtraction of detector scatter does not justify removal of this c omponent at the expense of sensitivity.