Use of a deep-learning-based lumen extraction method to detect significant stenosis on coronary computed tomography angiography in patients with severe coronary calcification.
Hidekazu InageNobuo TomizawaYujiro OtsukaChihiro AoshimaYuko KawaguchiKazuhisa TakamuraRie MatsumoriYuki KamoYui NozakiDaigo TakahashiAyako KudoMakoto HikiYosuke KogureShinichiro FujimotoTohru MinaminoShigeki AokiPublished in: The Egyptian heart journal : (EHJ) : official bulletin of the Egyptian Society of Cardiology (2022)
These findings suggest that the DL-LEM may improve the diagnostic performance in detecting significant stenosis in patients with severe coronary calcification. In addition, the results suggest that not a small medical economic effect can be expected.
Keyphrases
- coronary artery
- coronary artery disease
- deep learning
- chronic kidney disease
- early onset
- healthcare
- aortic stenosis
- machine learning
- heart failure
- computed tomography
- artificial intelligence
- magnetic resonance imaging
- drug induced
- ultrasound guided
- convolutional neural network
- magnetic resonance
- ejection fraction
- atrial fibrillation
- life cycle