Simultaneous segmentation, kinetic parameter estimation, and uncertainty visualization of dynamic PET images.
We develop a segmentation technique for dynamic PET incorporating the physiological parameters for different regions via kinetic modeling. We demonstrate the usefulness of our technique on fifteen [11C]Raclopride simulated PET images. We show qualitatively and quantitatively that the physiologically based algorithm outperforms two classical segmentation techniques. Further, we derive a formula to compute and visualize the uncertainty encountered during the segmentation.
Medical Image Analysis Lab, School of Computing Science, Simon Fraser University, Canada. aasaad@cs.sfu.ca
Ahmed
A
Saad
Ben
B
Smith
Ghassan
G
Hamarneh
Torsten
T
Möller
D000465:Algorithms; D001921:Brain / Q000000981:diagnostic imaging* / Q000378:metabolism*; D001931:Brain Mapping / Q000379:methods; D003196:Computer Graphics; D003198:Computer Simulation; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods; D021621:Imaging, Three-Dimensional / Q000379:methods; D007700:Kinetics; D008657:Metabolic Clearance Rate; D008954:Models, Biological; D015233:Models, Statistical; D010363:Pattern Recognition, Automated / Q000379:methods*; D049268:Positron-Emission Tomography / Q000379:methods*; D020891:Raclopride / Q000493:pharmacokinetics*; D019275:Radiopharmaceuticals / Q000493:pharmacokinetics; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D014584:User-Computer Interface
D019275:Radiopharmaceuticals; D020891:Raclopride