Title :
A Maximum NEC Criterion for Compton Collimation to Accurately Identify True Coincidences in PET
Author :
Chinn, Garry ; Levin, Craig S.
Author_Institution :
Radiol. Dept., Stanford Univ., Stanford, CA, USA
fDate :
7/1/2011 12:00:00 AM
Abstract :
In this work, we propose a new method to increase the accuracy of identifying true coincidence events for positron emission tomography (PET). This approach requires 3-D detectors with the ability to position each photon interaction in multi-interaction photon events. When multiple interactions occur in the detector, the incident direction of the photon can be estimated using the Compton scatter kinematics (Compton Collimation). If the difference between the estimated incident direction of the photon relative to a second, coincident photon lies within a certain angular range around colinearity, the line of response between the two photons is identified as a true coincidence and used for image reconstruction. We present an algorithm for choosing the incident photon direction window threshold that maximizes the noise equivalent counts of the PET system. For simulated data, the direction window removed 56%-67% of random coincidences while retaining >; 94% of true coincidences from image reconstruction as well as accurately extracted 70% of true coincidences from multiple coincidences.
Keywords :
Compton effect; Monte Carlo methods; image reconstruction; medical image processing; positron emission tomography; Compton collimation; Compton scatter kinematics; Monte Carlo simulation; PET; image reconstruction; maximum NEC criterion; noise equivalent counts; positron emission tomography; true coincidences; Detectors; Energy resolution; Image reconstruction; Monte Carlo methods; Photonics; Positron emission tomography; Spatial resolution; 3-D positioning detector; Compton collimation; Monte Carlo simulation; iterative image reconstruction; multiple photon coincidences; noise equivalent counts (NEC); positron emission tomography (PET); random coincidences; Algorithms; Breast; Cadmium; Female; Humans; Image Processing, Computer-Assisted; Monte Carlo Method; Phantoms, Imaging; Positron-Emission Tomography; Semiconductors; Tellurium; Zinc;
Journal_Title :
Medical Imaging, IEEE Transactions on
DOI :
10.1109/TMI.2011.2113379