Institute of Medical Device and Imaging, College of Medicine, National Taiwan University, No.1, Sec. 1, Jen Ai Rd., Zhongzheng Dist., Taipei City 100, Taiwan.
J Digit Imaging. 2022 Aug;35(4):834-845. doi: 10.1007/s10278-022-00606-x. Epub 2022 Mar 3.
Parametric imaging obtained from kinetic modeling analysis of dynamic positron emission tomography (PET) data is a useful tool for quantifying tracer kinetics. However, pixel-wise time-activity curves have high noise levels which lead to poor quality of parametric images. To solve this limitation, we proposed a new image denoising method based on deep image prior (DIP). Like the original DIP method, the proposed DIP method is an unsupervised method, in which no training dataset is required. However, the difference is that our method can simultaneously denoise all dynamic PET images. Moreover, we propose a modified version of the DIP method called double DIP (DDIP), which has two DIP architectures. The additional DIP model is used to generate high-quality input data for the second DIP model. Computer simulations were performed to evaluate the performance of the proposed DIP-based methods. Our simulation results showed that the DDIP method outperformed the single DIP method. In addition, the DDIP method combined with data augmentation could generate PET parametric images with superior image quality compared to the spatiotemporal-based non-local means filtering and high constrained backprojection. Our preliminary results show that our proposed DDIP method is a novel and effective unsupervised method for simultaneously denoising dynamic PET images.
基于动态正电子发射断层扫描（PET）数据的动力学建模分析获得的参数成像，是量化示踪剂动力学的有用工具。然而，像素级时间活性曲线具有较高的噪声水平，导致参数图像质量较差。为了解决这一限制，我们提出了一种基于深度图像先验（DIP）的新的图像去噪方法。与原始的 DIP 方法一样，所提出的 DIP 方法是一种无监督方法，不需要训练数据集。然而，不同的是，我们的方法可以同时对所有动态 PET 图像进行去噪。此外，我们提出了一种称为双 DIP（DDIP）的 DIP 方法的改进版本，该方法具有两个 DIP 架构。附加的 DIP 模型用于为第二个 DIP 模型生成高质量的输入数据。进行了计算机模拟以评估基于 DIP 的方法的性能。我们的模拟结果表明，DDIP 方法优于单 DIP 方法。此外，DDIP 方法结合数据增强可以生成与基于时空的非局部均值滤波和高约束反向投影相比具有更高图像质量的 PET 参数图像。我们的初步结果表明，我们提出的 DDIP 方法是一种新颖而有效的用于同时去噪动态 PET 图像的无监督方法。
