Cheng Zhibiao, Wen Junhai, Huang Gang, Yan Jianhua
Department of Biomedical Engineering, School of Life Science, Beijing Institute of Technology, Beijing, China.
Shanghai Key Laboratory of Molecular Imaging, Shanghai University of Medicine and Health Sciences, Shanghai, China.
Quant Imaging Med Surg. 2021 Jun;11(6):2792-2822. doi: 10.21037/qims-20-1078.
Recently, the application of artificial intelligence (AI) in medical imaging (including nuclear medicine imaging) has rapidly developed. Most AI applications in nuclear medicine imaging have focused on the diagnosis, treatment monitoring, and correlation analyses with pathology or specific gene mutation. It can also be used for image generation to shorten the time of image acquisition, reduce the dose of injected tracer, and enhance image quality. This work provides an overview of the application of AI in image generation for single-photon emission computed tomography (SPECT) and positron emission tomography (PET) either without or with anatomical information [CT or magnetic resonance imaging (MRI)]. This review focused on four aspects, including imaging physics, image reconstruction, image postprocessing, and internal dosimetry. AI application in generating attenuation map, estimating scatter events, boosting image quality, and predicting internal dose map is summarized and discussed.
近年来，人工智能（AI）在医学成像（包括核医学成像）中的应用迅速发展。核医学成像中的大多数AI应用都集中在诊断、治疗监测以及与病理学或特定基因突变的相关性分析上。它还可用于图像生成，以缩短图像采集时间、减少注射示踪剂的剂量并提高图像质量。这项工作概述了AI在单光子发射计算机断层扫描（SPECT）和正电子发射断层扫描（PET）图像生成中的应用，无论是否有解剖学信息[计算机断层扫描（CT）或磁共振成像（MRI）]。本综述聚焦于四个方面，包括成像物理学、图像重建、图像后处理和内照射剂量学。总结并讨论了AI在生成衰减图、估计散射事件、提高图像质量和预测内照射剂量图方面的应用。
