Influence of a novel deep-learning based reconstruction software on the objective and subjective image quality in low-dose abdominal computed tomography.
Andrea SteuweMarie WeberOliver Thomas BethgeChristin RademacherMatthias BoschheidgenLino Morris SawickiGerald AntochJoel AissaPublished in: The British journal of radiology (2020)
The assessed software reduces image noise by up to 27% compared to IR and 48% compared to FBP while maintaining the image information.The reduced image noise allows for a potential dose reduction of approximately 20% in abdominal imaging.
Keyphrases
- deep learning
- image quality
- computed tomography
- low dose
- artificial intelligence
- convolutional neural network
- air pollution
- dual energy
- machine learning
- positron emission tomography
- magnetic resonance imaging
- high dose
- healthcare
- sleep quality
- physical activity
- health information
- mass spectrometry
- depressive symptoms
- human health