3-DIMENSIONAL IMAGE-RECONSTRUCTION FOR PET BY MULTISLICE REBINNING AND AXIAL IMAGE FILTERING

A fast method is described for reconstructing volume images from three -dimensional (3D) coincidence data in positron emission tomography (PE T). The reconstruction method makes use of all coincidence data acquir ed by high-sensitivity PET systems that do not have inter-slice absorb ers (septa) to restrict the axial acceptance angle. The reconstruction method requires only a small amount of storage and computation, makin g it well suited for dynamic and whole-body studies. The method consis ts of three steps: (i) rebinning of coincidence data into a stack of 2 D sinograms; (ii) slice-by-slice reconstruction of the sinogram associ ated with each slice to produce a preliminary 3D image having strong b lurring in the axial (z) direction, but with different blurring at dif ferent z positions; and (iii) spatially variant filtering of the 3D im age in the axial direction (i.e. 1D filtering in z for each x-y column ) to produce the final image. The first step involves a new form of th e rebinning operation in which multiple sinograms are incremented for each oblique coincidence line (multi-slice rebinning). The axial filte ring step is formulated and implemented using the singular value decom position (SVD). The method has been applied successfully to simulated data and to measured data for different kinds of phantom (multiple poi nt sources, multiple discs, a cylinder with cold spheres, and a 3D bra in phantom).