The Influence of Noise in Dynamic PET Direct Reconstruction

In the present work a study is carried out in order to assess the efficiency of the direct reconstruction algorithms on noisy dynamic PET data. The study is performed via Monte Carlo simulations of a uniform cylindrical phantom whose emission values change in time according to a kinetic law. After generating the relevant projection data and properly adding the effects of different noise sources on them, the direct reconstruction and parametric estimation algorithm is applied. The resulting kinetic parameters and reconstructed images are then quantitatively evaluated with appropriate indexes. The simulation is repeated considering different sources of noise and different values of them. The results obtained allow us to affirm that the direct reconstruction algorithm tested maintains a good efficiency also in presence of noise.

[1]  Akihiko Uchiyama,et al.  MAP-based kinetic analysis for voxel-by-voxel compartment model estimation: Detailed imaging of the cerebral glucose metabolism using FDG , 2006, NeuroImage.

[2]  Jeffrey A. Fessler,et al.  Statistical image reconstruction methods for randoms-precorrected PET scans , 1998, Medical Image Anal..

[3]  Kris Thielemans,et al.  A survey of approaches for direct parametric image reconstruction in emission tomography. , 2008, Medical physics.

[4]  Guobao Wang,et al.  An Optimization Transfer Algorithm for Nonlinear Parametric Image Reconstruction From Dynamic PET Data , 2012, IEEE Transactions on Medical Imaging.

[5]  Richard M. Leahy,et al.  Patlak Image Estimation From Dual Time-Point List-Mode PET Data , 2014, IEEE Transactions on Medical Imaging.

[6]  Luigi Landini,et al.  Dynamic PET Data Generation and Analysis Software Tool for Evaluating the SNR Dependence on Kinetic Parameters Estimation , 2015 .

[7]  S. Dai,et al.  A pseudo-Poisson noise model for simulation of positron emission tomographic projection data. , 1992, Medical physics.

[8]  Jeffrey A. Fessler,et al.  Emission image reconstruction for randoms-precorrected PET allowing negative sinogram values , 2004, IEEE Transactions on Medical Imaging.

[9]  F. Turkheimer,et al.  Kinetic modeling in positron emission tomography. , 2002, The quarterly journal of nuclear medicine : official publication of the Italian Association of Nuclear Medicine (AIMN) [and] the International Association of Radiopharmacology.