In this work, we developed a novel text-guided image synthesis technique
which could generate realistic tau PET images from textual descriptions and the
subject's MR image. The generated tau PET images have the potential to be used
in examining relations between different measures and also increasing the
public availability of tau PET datasets. The method was based on latent
diffusion models. Both textual descriptions and the subject's MR prior image
were utilized as conditions during image generation. The subject's MR image can
provide anatomical details, while the text descriptions, such as gender, scan
time, cognitive test scores, and amyloid status, can provide further guidance
regarding where the tau neurofibrillary tangles might be deposited. Preliminary
experimental results based on clinical [18F]MK-6240 datasets demonstrate the
feasibility of the proposed method in generating realistic tau PET images at
different clinical stages.

本文提出了一种基于文本的图像合成技术，利用主题的 MR 映像和文字描述来生成逼真的 tau PET 影像，该方法基于潜在扩散模型。利用身体图像提供解剖细节，而文本描述可以提供有关 tau 神经纤维缠结可能沉积的位置的指导，初步的实验结果证明了该方法生成真实的 tau PET 影像的可行性。