Deep learning-based atherosclerotic coronary plaque segmentation on coronary CT angiography.
Natasa JávorszkyBálint HomonnayGary GerstenblithDavid BluemkePéter KissMihály TörökDavid CelentanoHong LaiShenghan LaiMárton KolossváryPublished in: European radiology (2022)
• Deep learning 3D U-net model for coronary segmentation achieves comparable results with expert readers' volumetric plaque quantification. • Transfer learning may be needed to achieve similar results for other scanner and plaque characteristics. • The developed deep learning algorithm is open-source and may be implemented in any CT analysis software.
Keyphrases
- deep learning
- coronary artery disease
- convolutional neural network
- coronary artery
- artificial intelligence
- machine learning
- image quality
- computed tomography
- aortic stenosis
- magnetic resonance imaging
- contrast enhanced
- magnetic resonance
- positron emission tomography
- transcatheter aortic valve replacement
- aortic valve
- ejection fraction