Recent research has showed that attenuation images can be determined from emission data, jointly with activity images, up to a scaling constant when utilizing the time-of-flight (TOF) information. We aim to develop practical CT-less joint reconstruction for clinical TOF PET scanners to obtain quantitatively accurate activity and attenuation images. In this work, we present a joint reconstruction of activity and attenuation based on MLAA (maximum likelihood reconstruction of attenuation and activity) with autonomous scaling determination and joint TOF scatter estimation from TOF PET data. Our idea for scaling is to use a selected volume of interest (VOI) in a reconstructed attenuation image with known attenuation, e.g. a liver in patient imaging. First, we construct a unit attenuation medium which has a similar, though not necessarily the same, support to the imaged emission object. All detectable LORs intersecting the unit medium have an attenuation factor of e ⁻¹≈ 0.3679, i.e. the line integral of linear attenuation coefficients is one. The scaling factor can then be determined from the difference between the reconstructed attenuation image and the known attenuation within the selected VOI normalized by the unit attenuation medium. A four-step iterative joint reconstruction algorithm is developed. In each iteration, (1) first the activity is updated using TOF OSEM from TOF list-mode data; (2) then the attenuation image is updated using XMLTR—a extended MLTR from non-TOF LOR sinograms; (3) a scaling factor is determined based on the selected VOI and both activity and attenuation images are updated using the estimated scaling; and (4) scatter is estimated using TOF single scatter simulation with the jointly reconstructed activity and attenuation images. The performance of joint reconstruction is studied using simulated data from a generic whole-body clinical TOF PET scanner and a long axial FOV research PET scanner as well as 3D experimental data from the PennPET Explorer scanner. We show that the proposed joint reconstruction with proper autonomous scaling provides low bias results comparable to the reference reconstruction with known attenuation.

最近的研究表明，在利用飞行时间（TOF）信息时，可以根据发射数据以及活动图像确定衰减图像，直到比例缩放常数为止。我们旨在为临床TOF PET扫描仪开发实用的无CT关节重建术，以获得定量准确的活动和衰减图像。在这项工作中，我们提出了基于MLAA（衰减和活动的最大似然重建）的活动和衰减的联合重建，并具有自动缩放比例确定和来自TOF PET数据的联合TOF散射估计。我们缩放的想法是在具有已知衰减的重建衰减图像（例如患者成像中的肝脏）中使用选定的感兴趣体积（VOI）。首先，我们构造一个单位衰减介质，它具有相似的（但不一定相同），支持成像的发射对象。所有与单位介质相交的可检测LOR的衰减因子为e ^-1≈0.3679，即线性衰减系数的线积分为1。然后可以从重构的衰减图像与通过单位衰减介质归一化的所选VOI内的已知衰减之间的差异确定比例因子。提出了一种四步迭代联合重建算法。在每次迭代中，（1）首先使用TOF OSEM从TOF列表模式数据更新活动；（2）然后使用XMLTR更新衰减图像-来自非TOF LOR正弦图的扩展MLTR；（3）基于选择的VOI确定比例因子，并使用估计的比例来更新活动图像和衰减图像；（4）使用TOF单散射模拟和联合重建的活动和衰减图像估算散射。使用通用全身临床TOF PET扫描仪和长轴FOV研究PET扫描仪的模拟数据以及PennPET Explorer扫描仪的3D实验数据，研究了关节重建的性能。我们表明，提出的具有适当自主缩放比例的联合重建可提供与已知衰减的参考重建相当的低偏差结果。