Clinical validation of an AI-based motion correction reconstruction algorithm in cerebral CT.
Leilei ZhouHao LiuYi-Xuan ZouGuozhi ZhangBin SuLiyan LuYu-Chen ChenXindao YinHong-Bing JiangPublished in: European radiology (2022)
• An artificial intelligence-based motion correction (MC) reconstruction algorithm has been clinically validated in both qualitative and quantitative manner. • The MC algorithm reduces motion artifacts in cerebral CT and increases the diagnostic confidence for brain lesions. • The MC algorithm can help avoiding rescans caused by motion and improving the efficiency of cerebral CT in the emergency department.
Keyphrases
- artificial intelligence
- machine learning
- deep learning
- image quality
- emergency department
- dual energy
- subarachnoid hemorrhage
- big data
- computed tomography
- contrast enhanced
- high speed
- cerebral ischemia
- positron emission tomography
- neural network
- magnetic resonance imaging
- high resolution
- systematic review
- brain injury
- magnetic resonance
- multiple sclerosis
- blood brain barrier
- cerebral blood flow
- mass spectrometry