%0 Journal Article
%T Evaluation of the Feasibility and Quantitative Accuracy of a Generalized Scatter 2D PET Reconstruction Method
%A Hongyan Sun
%A Stephen Pistorius
%J ISRN Biomedical Imaging
%D 2013
%R 10.1155/2013/943051
%X Scatter degrades the contrast and quantitative accuracy of positron emission tomography (PET) images, and most methods for estimating and correcting scattered coincidences in PET subtract scattered events from the measured data. Compton scattering kinematics can be used to map out the locus of possible scattering locations. These curved lines (2D) or surfaces (3D), which connect the coincidence detectors, encompass the surface (2D) or volume (3D) where the decay occurs. In the limiting case where the scattering angle approaches zero, the scattered coincidence approaches the true coincidence. Therefore, both true and scattered coincidences can be considered similarly in a generalized scatter maximum-likelihood expectation-maximization reconstruction algorithm. The proposed method was tested using list-mode data obtained from a GATE simulation of a Jaszczak-type phantom. For scatter fractions from 10% to 60%, this approach reduces noise and improves the contrast recovery coefficients by 0.5每3.0% compared with reconstructions using true coincidences and by 3.0每24.5% with conventional reconstruction methods. The results demonstrate that this algorithm is capable of producing images entirely from scattered photons, eliminates the need for scatter corrections, increases image contrast, and reduces noise. This could be used to improve diagnostic quality and/or to reduce patient dose and radiopharmaceutical cost. 1. Introduction Compton scattering degrades image contrast and compromises quantitative accuracy in positron emission tomography (PET) [1, 2]. Scattered coincidences are typically considered as noise which reduces PET image quality. This issue is more serious when operating in 3D mode without slice-defining septa and in large patients, where the scatter fraction can be as high as 40每60% [3每6]. Consequently a number of approaches for estimating and correcting scattered coincidences in PET data have been proposed [3, 7每19]. Most of these techniques estimate a scatter sinogram, which is used to subtract the scatter from the projection data [20] in precorrection methods [21] or as a constant additive term incorporated in a reconstruction algorithm [22每24]. Inaccuracy in the estimation of the scatter sinogram will introduce significant biases in the activity distribution [6]. The subtraction-based correction methods destroy the Poisson nature of the data, reduce the system＊s sensitivity, and amplify image noise [3, 25]. With list-mode acquisitions in modern PET and improved detector technology, the use of the energy of individual photons becomes feasible
%U http://www.hindawi.com/journals/isrn.biomedical.imaging/2013/943051/