Paper Info
Title
List mode reconstruction for PET with motion compensation: a simulation study
Abstract
Motion artifacts can be a significant factor that limits the image quality in high-resolution PET. Surveillance systems have been developed to track the movements of the subject during a scan. Development of reconstruction algorithms that are able to compensate for the subject motion will increase the potential of PET. In this paper we present a list mode likelihood reconstruction algorithm with the ability of motion compensation. The subject motion is explicitly modeled in the likelihood function. The detections of each detector pair are modeled as a Poisson process with time-varying rate function. The proposed method has several advantages over the existing methods. It uses all detected events and does not introduce any interpolation error. Computer simulations show that the proposed method can compensate simulated subject movements and that the reconstructed images have no visible motion artifacts.
Year
DOI
Venue
2002
10.1109/ISBI.2002.1029282
ISBI
Keywords
Field
DocType
human brain imaging,motion compensation,poisson distribution,list mode likelihood reconstruction algorithm,image quality,medical signal detection,poisson process,image resolution,maximum likelihood estimation,time-varying rate function,interpolation error,detector pair,reconstruction algorithms,high-resolution pet,motion estimation,motion artifacts,image reconstruction,positron emission tomography,subject motion,brain,simulation study,surveillance systems,subject movement tracking,list mode reconstruction,medical image processing,interpolation,simulation,detectors,likelihood function,computer simulation,high resolution,algorithms,tracking
Iterative reconstruction,Computer vision,Quarter-pixel motion,Motion field,Computer science,Interpolation,Motion compensation,Image quality,Reconstruction algorithm,Artificial intelligence,Motion estimation
Conference
ISBN
Citations 
PageRank 
0-7803-7584-X
3
0.60
References 
Authors
2
2
Name
Order
Citations
PageRank
Jinyi Qi128435.82
R H Huesman2549.34