PET calibration method of nonlinear position estimation algorithms for continuous NaI(Tl) crystals

This paper presents a calibration method for obtaining data to adjust nonlinear position estimation algorithms. This procedure is based on two measurements utilizing specialized collimators and a background subtraction algorithm. Since this method does not require electronic collimation, each PET detector module can be calibrated using a source of gamma-rays with a simple measurement setup. A nonlinear position estimation algorithm based in Artificial Neural Networks (ANNs) was evaluated. Its adjustment measurements were obtained utilizing this calibration method with a low cost PET detector module. The detector module consists of a continuous NaI(Tl) crystal, attached to an array of 6×8 Hamamatsu R1534 Photomultiplier tubes (PMTs). Compared to Anger logic, the ANNs showed an improvement in the spatial resolution as well as a decrease of the edge packing effect. The experimental setups were designed and validated with GATE software.