噪声对PET图像质量的影响研究

Research on Noise Impact on Quality of Pet Images

研究PET图像噪声与质量的关系,作为选择最适当的PET重建迭代次数或迭代停止的依据.利用蒙特卡罗模拟Siemens ECAT PET扫描仪,用OSEM、MLEM迭代重建算法获得Huffman、Utah重建图像,使用了SSIM、PSNR两种不同质量评价方法估算图像质量并以标准偏差评估噪声.结果显示Huffman图像噪声随着迭代次数增加,图像质量随着迭代次数降低;均值滤波除燥会降低图像质量;利用Utah重建图像进行再度计算也得同样结果.说明噪声影响到图像质量的计算,噪声滤除会造成最优图像的计算错误.精准的估算噪声并且有效的滤除,将可获得真正最优迭代图像,作为停止迭代依据.

The image noise affected the results of quality estimation in PET image was investigated in this research. The best image quality can be used to find the adequate iteration numbers in PET image reconstruction process. Two phantoms, Huffman and Utah, were used in this research. The simulation was processed by using a Monte Carlo algorithm to simulate phantom in a Siemens ECAT PET scanner respectively. Flowering that an MLEM iterative algorithm named OSEM was used for reconstruction. The noise level on image was estimated by standard deviation calculation. The image quality evaluation used the SSIM and the PSNR two image quality indices. The noise in PET images is ascending with the iteration numbers increasing but the image quality contradicts to the numbers of iteration for a Huffman phantom. The image quality of filtered images, by using average filter, is significantly lower than the original images. This effect indicated that the noise affects the image quality calculations. Optimal quality of image appears later than the unfiltered image, which shows that the rising noise results in the optimal image detection. A Utah phantom was also used to examine this effect and got equal results. The noise in image estimated accurately the truly optimal iterative image can be finding easily.