FIGURES OF MERIT FOR COMPARING RECONSTRUCTION ALGORITHMS WITH A VOLUME-IMAGING PET SCANNER

For volume-imaging PET scanners, no septa are used to maximize the sensitivity by collecting events oblique to the scanner axis. We answer two questions: (i) how does the performance of an image reconstruction algorithm for a volume-imaging PET scanner depend on its general dimensions? and (ii) at what point is a three-dimensional (3D) reconstruction algorithm needed for a volume-imaging scanner, as the axial extent is increased? A 3D reconstruction algorithm will accurately incorporate the oblique events in a reconstruction of the original source distribution. From simulations of an existing volume PET scanner with a maximum axial acceptance angle (+/-alpha) of alpha = 9 degrees, however, we show that the single-slice rebinning algorithm is a good compromise between sensitivity, speed, and accuracy when compared to standard two-dimensional reconstruction (alpha = 1 degrees), and a 3D reconstruction with alpha = 9 degrees. We also show with simulations that a new scanner with alpha = 27 degrees requires 3D, reconstruction in order to achieve maximum sensitivity without unacceptable losses in accuracy. Measurements of scanner performance are based on a series of figures of merit that characterize image quality and quantitative accuracy measured from a set of simulated test phantoms.