List mode reconstruction for PET with motion compensation: A simulation study
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 moti is explicitly modeled in the likelihood function. The detections of each detector pair are modeled as a Poisson process with time vary ingrate 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.
- Research Organization:
- Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
- Sponsoring Organization:
- USDOE Director, Office of Science. Biological and Environmental Research, Medical Science Division (US)
- DOE Contract Number:
- AC03-76SF00098
- OSTI ID:
- 815495
- Report Number(s):
- LBNL-51930; R&D Project: 440H01; TRN: US0304631
- Resource Relation:
- Conference: IEEE International Symposium on Biomedical Imaging, Washington, DC (US), 07/07/2002--07/10/2002; Other Information: PBD: 3 Jul 2002
- Country of Publication:
- United States
- Language:
- English
Similar Records
WE-AB-204-09: Respiratory Motion Correction in 4D-PET by Simultaneous Motion Estimation and Image Reconstruction (SMEIR)
Relative role of motion and PSF compensation in whole-body oncologic PET-MR imaging