【摘要】 散射事件是影响正电子发射断层扫描术 (Positron emission tomography,PET)图像重建质量的一个重要因素。我们根据投影图像的分布特征 ,基于泊松数据模型 ,利用最大似然期望值法 (Maximum likelihoodexpectation maximization,ML EM)对正弦图进行散射校正。比较采用 ML EM方法和去卷积法进行散射校正后的正弦图以及重建图像 ,结果表明我们的方法在进行散射补偿的同时 ,增加了图像的对比度 ,效果优于传统的校正方法更多还原

【Abstract】 Scatter coincident events are the important factor that affects the quality of positron emission tomography(PET) images. In this paper, according to the characters of projection data, a scatter correction method which uses maximum likelihood expectation maximization(MLEM)algorithm based on poisson model is proposed. We compared the sinograms and reconstructed images corrected by MLEM algorithm and deconvolution method respectively. The results indicate that the algorithm proposed in this paper increases the contrast of images while correcting scatter. It is better than the traditional method.更多还原