ABSTRACT
PURPOSE: To establish the methods for sinogram formation and correction in order to appropriately apply the filtered backprojection (FBP) reconstruction algorithm to the data acquired using PET scanner with multiple scintillation crystal layers. MATERIAL AND METHODS: Formation for raw PET data storage and conversion methods from listmode data to histogram and sinogram were optimized. To solve the various problems occurred while the raw histogram was converted into sinogram, optimal sampling strategy and sampling efficiency correction method were investigated. Gap compensation methods that is unique in this system were also investigated. All the sinogram data were reconstructed using 2D filtered backprojection algorithm and compared to estimate the improvements by the correction algorithms. RESULTS: Optimal radial sampling interval and number of angular samples in terms of the sampling theorem and sampling efficiency correction algorithm were pitch/2 and 120, respectively. By applying the sampling efficiency correction and gap compensation, artifacts and background noise on the reconstructed image could be reduced. CONCLUSION: Conversion method from the histogram to sinogram was investigated for the FBP reconstruction of data acquired using multiple scintillation crystal layers. This method will be useful for the fast 2D reconstruction of multiple crystal layer PET data.
Subject(s)
Artifacts , Compensation and Redress , Information Storage and Retrieval , NoiseABSTRACT
PURPOSE: The goal of this paper is to present the design and performance of a position encoding circuit for 16 x 16 array of position sensitive multi-anode photomultiplier tube for small animal PET scanners. This circuit which reduces the number of readout channels from 256 to 4 channels is based on a charge division method utilizing a resistor array. MATERIALS AND METHODS: The position encoding circuit was simulated with PSpice before fabrication. The position encoding circuit reads out the signals from H9500 flat panel PMTs (Hamamatsu Photonics K.K., Japan) on which 1.5 x 1.5 x 7.0 mm3 L0.9GSO (Lu1.8Gd0.2SiO5:Ce) crystals were mounted. For coincidence detection, two different PET modules were used. One PET module consisted of a 29 x 29 L0.9GSO crystal layer, and the other PET module two 28 x 28 and 29 x 29 L0.9GSO crystal layers which have relative offsets by half a crystal pitch in x- and y-directions. The crystal mapping algorithm was also developed to identify crystals. RESULTS: Each crystal was clearly visible in flood images. The crystal identification capability was enhanced further by changing the values of resistors near the edge of the resistor array. Energy resolutions of individual crystal were about 11.6%(SD 1.6). The flood images were segmented well with the proposed crystal mapping algorithm. CONCLUSION: The position encoding circuit resulted in a clear separation of crystals and sufficient energy resolutions with H9500 flat-panel PMT and L0.9GSO crystals. This circuit is good enough for use in small animal PET scanners.