Michielsen Koen, Nuyts Johan
Department of Imaging and Pathology, Division of Nuclear Medicine and Molecular Imaging, KU Leuven, Leuven 3000, Belgium and Medical Imaging Research Center, KU Leuven, Leuven 3000, Belgium.
Med Phys. 2015 Nov;42(11):6537-48. doi: 10.1118/1.4933247.
The authors wish to evaluate the possible advantages of using a multigrid approach to maximum-a-posteriori reconstruction in digital breast tomosynthesis together with block-iterative updates in the form of either plane-by-plane updates or ordered subsets.
The authors previously developed a penalized maximum likelihood reconstruction algorithm with resolution model dedicated to breast tomosynthesis [K. Michielsen et al., "Patchwork reconstruction with resolution modeling for digital breast tomosynthesis," Med. Phys. 40, 031105 (10pp.) (2013)]. This algorithm was extended with ordered subsets and multigrid updates, and the effects on the convergence and on limited angle artifact appearance were evaluated on a mathematical phantom and patient data. To ensure a fair comparison, the analysis was performed at the same computational cost for all methods. To assess convergence and artifact creation in the phantom reconstructions, the authors looked at posterior likelihood, sum of squared residuals, contrast of identical calcifications at different positions, and the standard deviation between the contrasts of these calcifications. For the patient cases, the authors calculated posterior likelihood, measured the signal difference to noise ratio of subtle microcalcifications, and visually evaluated the reconstructions.
The authors selected multigrid sequences scoring in the best 10% of the four evaluated parameters, except for the reconstructions with subsets where a low standard deviation of the contrast was incompatible with the three other parameters. In further evaluation of phantom reconstructions from noisy data and patient data, the authors found improved convergence and a reduction in artifacts for our chosen multigrid reconstructions compared to the single grid reconstructions with equivalent computational cost, although there was a diminishing return for an increasing number of subsets.
Multigrid reconstruction improves upon reconstruction with a fixed grid when evaluated at a fixed computational cost. For multigrid reconstruction, using plane-by-plane updates or applying ordered subsets resulted in similar performance.
作者希望评估在数字乳腺断层合成中使用多重网格方法进行最大后验重建以及采用逐平面更新或有序子集形式的块迭代更新的潜在优势。
作者之前开发了一种带有分辨率模型的惩罚最大似然重建算法，专门用于乳腺断层合成[K. 米希尔森等人，“用于数字乳腺断层合成的具有分辨率建模的拼凑重建”，《医学物理》40, 031105 (10页) (2013)]。该算法扩展了有序子集和多重网格更新，并在数学模型和患者数据上评估了其对收敛性和有限角度伪影出现的影响。为确保公平比较，对所有方法都以相同的计算成本进行分析。为评估模型重建中的收敛性和伪影生成，作者观察了后验似然、残差平方和、不同位置相同钙化的对比度以及这些钙化对比度之间的标准差。对于患者病例，作者计算了后验似然，测量了微小钙化的信号噪声比，并对重建结果进行了视觉评估。
作者选择了在四个评估参数中得分处于最佳10%的多重网格序列，但对于具有子集的重建，对比度的低标准差与其他三个参数不兼容。在对来自噪声数据和患者数据的模型重建进行进一步评估时，作者发现与具有等效计算成本的单网格重建相比，我们选择的多重网格重建具有更好的收敛性且伪影减少，尽管随着子集数量的增加收益递减。
在固定计算成本下进行评估时，多重网格重建比固定网格重建有所改进。对于多重网格重建，采用逐平面更新或应用有序子集产生的性能相似。
