Accuracy of a deep learning-based algorithm for the detection of thoracic aortic calcifications in chest computed tomography and cardiovascular surgery planning.
Ruben SaffarJonathan I SperlTim BergerJana VojtekovaMaximilian KreibichMuhammad Taha HagarJakob B WeissMartin SoschynskiFabian BambergMartin CzernyChristopher SchuppertChristopher L SchlettPublished in: European journal of cardio-thoracic surgery : official journal of the European Association for Cardio-thoracic Surgery (2024)
Fully automated segmental detection of thoracic aortic calcifications in chest CT performs with high accuracy. This includes the critical preoperative assessment of the aortic clamping zone.
Keyphrases
- deep learning
- computed tomography
- aortic valve
- machine learning
- left ventricular
- pulmonary artery
- aortic dissection
- spinal cord
- loop mediated isothermal amplification
- positron emission tomography
- minimally invasive
- dual energy
- image quality
- magnetic resonance imaging
- real time pcr
- label free
- artificial intelligence
- contrast enhanced
- convolutional neural network
- patients undergoing
- coronary artery bypass
- heart failure
- magnetic resonance
- high throughput
- spinal cord injury
- coronary artery
- single cell