Application of Artificial Intelligence to Cardiovascular Computed Tomography.
Dong-Hyun YangPublished in: Korean journal of radiology (2021)
Cardiovascular computed tomography (CT) is among the most active fields with ongoing technical innovation related to image acquisition and analysis. Artificial intelligence can be incorporated into various clinical applications of cardiovascular CT, including imaging of the heart valves and coronary arteries, as well as imaging to evaluate myocardial function and congenital heart disease. This review summarizes the latest research on the application of deep learning to cardiovascular CT. The areas covered range from image quality improvement to automatic analysis of CT images, including methods such as calcium scoring, image segmentation, and coronary artery evaluation.
Keyphrases
- deep learning
- artificial intelligence
- computed tomography
- dual energy
- image quality
- contrast enhanced
- convolutional neural network
- coronary artery
- positron emission tomography
- big data
- machine learning
- congenital heart disease
- magnetic resonance imaging
- quality improvement
- high resolution
- pulmonary artery
- heart failure
- coronary artery disease
- magnetic resonance
- left ventricular
- photodynamic therapy
- patient safety
- mass spectrometry
- pet ct
- pulmonary arterial hypertension
- transcatheter aortic valve replacement
- atrial fibrillation
- pulmonary hypertension
- optical coherence tomography