# Assessment of MicroPET Image Quality Based on Reconstruction Methods and Post-Filtering
## 1 Introduction  
As a nuclear medicine functional imaging technique, positron emission tomography (PET) imaging is a powerful tool for diagnosis of tumor or cardiac function based on the estimation of metabolic processes. Unfortunately, the image accuracy of PET is relatively lower than that of other clinical imaging techniques such as magnetic resonance imaging (MRI) and computed tomography (CT) due to the intrinsic poor spatial resolution associated with the PET signal capturing principle. A physical solution is the development of gamma ray detectors (scintillator crystal) or signal processing circuits to correct for time of flight. Physical solutions are expensive and take a long time. We suggest an image correction method based on assessment of performance. Poor spatial resolution causes a partial volume effect (PVE) [1, 2, 3]. The accuracy of a PET image is affected by the PVE, resulting in image blurring and image sampling. Spill-in and spill-out (i.e., spillover) phenomena are generated by the PVE. The radioactivity of tissue may be underestimated due to spill-in from adjacent high-radioactivity tissue (e.g., tumor) [4]. The radioactivity of a volume of interest (VOI) may be overestimated due to spillover occurring into the VOI from high-radioactivity tissue (e.g., heart cavity). When analyzing cardiac perfusion in dynamic cardiac PET images, perfusion values change with time sequencing. The time-activity curve (TAC) peak of the myocardium is observed at full blood pool. However, the blood pool activity is maintained at a constant level from activity uptake in the myocardium, implying that the TAC of blood pool and myocardium is distorted by spillover and may need correction. Therefore, spillover creates difficulties in measuring myocardial blood flow (MBF) in cardiac PET analysis. The spillover phenomenon needs to be corrected using a recovery coefficient (RC). The RC value may be used in absolute measurement of myocardial blood flow (MBF) [5]. The RC, uniformity, and spillover ratio (SOR) of PET images are measured and assessed using the NEMA NU-4 phantom [6; 7; 8; 9; 10]. [PERSON] et al. introduced a simple PVE correction method in which the measured uptake value in the region of interest (ROI) was divided by a correction factor, RC. For smaller tumors, tumor uptake value may be underestimated due to the PVE, and this problem is addressed by RC adaption. The spillover effect observed in myocardium from blood pool may distort the time-activity curve (TAC) in myocardium upon cardiac PET imaging. The distortion of the TAC affects the measurement of MBF and needs correction. The myocardial TAC may be corrected using the RC because of myocardial thinning. Moreover, reconstruction methods have been developed and assessed for enhancement of PET image accuracy [11; 12; 13; 14]. The PVE is depended on PET image reconstruction methods. Various PET image reconstruction methods have been evaluated in PET studies and classified into analytical and iterative approaches. Analytical approaches include filtered back projection (FBP), Fourier rebinning (FORE), and three-dimensional reprojection (3 DRP). The iterative approaches include two- or three-dimensional ordered-subsets expectation maximization (OSEM2D or OSEM3D) and maximum likelihood expectation maximization (ML-EM) algorithms. Another study reported that an iterative reconstruction method was more accurate than analytical reconstruction methods for the absolute measurement of MBF [15]. [PERSON] et al. reported that the OSEM reconstruction method produced better image quality and less noise than the FBP reconstruction method [16]. [PERSON] et al. compared reconstruction methods (FBP, OSEM2D, OSEM3D, and 3 DRP) in cardiac PET imaging and reported that the OSEM3D reconstruction method showed a higher correlation with TTC staining and provided better image quality and contrast than other methods [17]. Post-filtering produces blurred images but can reduce the image noise. A filtering size larger than the image pixel size may result in image distortion.