Abstract: A PET event position calculation method using a combination angular and radial event map wherein identification of the radial distance of the event from the centroid of the scintillation crystal with which the event is associated as well as angular information is performed. The radial distance can be converted to a statistical confidence interval, which information can be used in downstream processing. More sophisticated reconstruction algorithms can use the confidence interval information selectively, to generate higher fidelity images with higher confidence information, and to improve statistics in dynamic imaging with lower confidence information.

Abstract: A crystal lookup table used to define a matching relationship between a signal position of a detected event in a PET scanner and a corresponding detector pixel location is generated using a neural network-based algorithm, and is implemented by a FPGA.

Abstract: A PET event position calculation method using a combination angular and radial event map wherein identification of the radial distance of the event from the centroid of the scintillation crystal with which the event is associated as well as angular information is performed. The radial distance can be converted to a statistical confidence interval, which information can be used in downstream processing. More sophisticated reconstruction algorithms can use the confidence interval information selectively, to generate higher fidelity images with higher confidence information, and to improve statistics in dynamic imaging with lower confidence information.

Abstract: A PET event position calculation method using a combination angular and radial event map wherein identification of the radial distance of the event from the centroid of the scintillation crystal with which the event is associated as well as angular information is performed. The radial distance can be converted to a statistical confidence interval, which information can be used in downstream processing. More sophisticated reconstruction algorithms can use the confidence interval information selectively, to generate higher fidelity images with higher confidence information, and to improve statistics in dynamic imaging with lower confidence information.

Abstract: A crystal lookup table used to define a matching relationship between a signal position of a detected event in a PET scanner and a corresponding detector pixel location is generated using a neural network-based algorithm, and is implemented by a FPGA.