Reducing pediatric total-body PET/CT imaging scan time with multimodal artificial intelligence technology.
Qiyang ZhangYingying HuChao ZhouYumo ZhaoNa ZhangYun ZhouYongfeng YangHairong ZhengWei FanDong LiangZhanli HuPublished in: EJNMMI physics (2024)
Multimodal artificial intelligence techniques can effectively improve the quality of pediatric total-body PET/CT images acquired using ultrashort scan times. This has the potential to decrease the use of sedation, enhance guardian confidence, and reduce the probability of motion artifacts.
Keyphrases
- pet ct
- artificial intelligence
- deep learning
- machine learning
- big data
- computed tomography
- positron emission tomography
- pain management
- convolutional neural network
- high resolution
- optical coherence tomography
- magnetic resonance imaging
- mechanical ventilation
- high speed
- image quality
- fluorescence imaging
- acute respiratory distress syndrome
- mass spectrometry
- magnetic resonance
- childhood cancer