摘要
为验证加型ART、ML-EM、Log熵三种算法在TGS发射图像重建实际测量中的适用性,开展了相关的实验研究。结果表明:为快速准确重建发射图像,ML-EM算法为最佳选择;当介质结块现象严重时Log熵迭代算法可以作为参考。由于实验介质存在结块现象,耗时相对较长的Log熵迭代算法反而优于ML-EM算法。该实验研究验证了发射图像重建方法的有效性,较好地解决了层析γ扫描发射图像重建这一关键技术。
Experimentatal research is carried out to evaluate the applicability in actual measurement to emission image reconstruction of Tomographic Gamma Scanning in the paper. The result indicates that maximum likeli- hood expectation - maximization algorithm is the best in fast emission image reconstruction and the logarithm entropy algorithm can be the preferance when the caking phenomenon in the medium is serious. In this experiment the logarithm entropy algorithm is more active than maximum likelihood expectation - maximization algorithm because of the caking phenomenon. The experimentatal research verifies the validity of the algorithms and well solves the key technology of emission image reconstruction of Tomographic Gamma Scanning.
出处
《核电子学与探测技术》
CAS
CSCD
北大核心
2012年第11期1276-1279,共4页
Nuclear Electronics & Detection Technology
基金
国家自然科学基金资助项目(10975183)
关键词
层析γ扫描
发射图像重建
实验研究
迭代重建算法
Tomographic Gamma Scanning
emission image reconstruction
experimentatal research
iterative reconstruction algorithms
