EVALUATION OF TASK-ORIENTED PERFORMANCE OF SEVERAL FULLY 3D PET RECONSTRUCTION ALGORITHMS
EVALUATION OF TASK-ORIENTED PERFORMANCE OF SEVERAL FULLY 3D PET RECONSTRUCTION ALGORITHMS
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DOI：
10.1088/0031-9155/39/3/004
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发表时间：
1994-03-01
影响因子：
3.5
通讯作者：
KINAHAN, PE
中科院分区：
文献类型：
--
作者：
MATEJ, S;HERMAN, GT;KINAHAN, PE
五个完全三维PET重建算法的相对性能进行了评估。该算法是一个过滤反投影（FBP）的方法和两个变种的EM-ML和ART迭代方法。对于每种迭代方法，一种变体使用体素，另一种变体使用“斑点”（在其边界上平滑衰减到零的球对称函数）作为其离散重建模型中的基函数。这些方法进行评估的角度来看，他们所产生的重建的三个典型的医疗任务估计的平均活动感兴趣的特定区域内，热点的检测，冷点的检测的功效。在五种算法的描述中允许使用自由参数;这些参数由训练过程确定，在训练过程中选择自由参数的值，该值（几乎）最大化技术品质因数。这种训练和实际的比较评估是通过使用随机生成的幻影和它们的投影数据来完成的。该方法允许分配水平的统计学意义的索赔的相对优势，一个算法比另一个特定的任务。我们发现，在迭代算法中使用斑点作为基函数肯定是优于使用体素。这一结果具有很高的统计学意义。(We也包括它的视觉说明）。比较FBP、使用Blob的EM-ML和使用Blob的ART，我们没有发现所研究的方法变体的整体性能有明显差异。如果有的话，我们的研究结果表明，使用斑点的ART可能是三种方法中最有效的。
The relative performance of five fully 3D PET reconstruction algorithms is evaluated. The algorithms are a filtered backprojection (FBP) method and two variants each of the EM-ML and ART iterative methods. For each of the iterative methods, one variant makes use of voxels and the other makes use of 'blobs' (spherically symmetric functions smoothly decaying to zero al their boundaries) as basis functions in its discrete reconstruction model. The methods are evaluated from the point of view of the efficacy of the reconstructions produced by them for three typical medical tasks-estimation of the average activity inside specific regions of interest, detection of hot spots, and detection of cold spots. A free parameter is allowed in the description of each of the five algorithms; the parameters are determined by a training process during which a value of the free parameter is selected which (nearly) maximizes a technical figure of merit. Such training and the actual comparative evaluation is done by making use of randomly generated phantoms and their projection data. The methodology allows assignation of levels of statistical significance to claims of the relative superiority of one algorithm over another for a particular task. We find that using blobs as basis functions in the iterative algorithms is definitely advantageous over using voxels. This result has high statistical significance. (We also include a visual illustration of it.) Comparing FBP, EM-ML using blobs, and ART using blobs, we do not find a clear difference in the overall performance of the investigated variants of the methods. If anything, our results suggest that ART using blobs may be the most efficacious of the three.