Title :
Statistical reconstruction-based scatter correction: a new method for 3D PET
Author_Institution :
Div. of Nucl. Med., Geneva Univ. Hospital, Switzerland
Abstract :
Accurate scatter correction is one of the major problems facing quantitative 3D PET and many methods have been developed for the purpose of reducing the resultant degradation of image contrast and loss of quantitative accuracy. A new scatter correction method called Statistical Reconstruction-Based Scatter Correction (SRBSC) is proposed in this paper and evaluated using Monte Carlo simulations, experimental phantoms and clinical studies. For accurate modeling, the scatter fraction and scatter response function for uniformly attenuating media are parametrised using Monte Carlo simulations
Keywords :
Monte Carlo methods; gamma-ray scattering; image reconstruction; medical image processing; positron emission tomography; statistics; 3D PET method; Monte Carlo simulations; clinical studies; experimental phantom studies; image contrast; image degradation reduction; medical diagnostic imaging; nuclear medicine; quantitative accuracy loss; statistical reconstruction-based scatter correction; uniformly attenuating media; Acceleration; Additive noise; Convergence; Degradation; Frequency; Image reconstruction; Iterative methods; Positron emission tomography; Reconstruction algorithms; Scattering parameters;
Conference_Titel :
Engineering in Medicine and Biology Society, 2000. Proceedings of the 22nd Annual International Conference of the IEEE
Conference_Location :
Chicago, IL
Print_ISBN :
0-7803-6465-1
DOI :
10.1109/IEMBS.2000.900675
