Diagnostic performance of deep learning-based vessel extraction and stenosis detection on coronary computed tomography angiography for coronary artery disease: a multi-reader multi-case study.
Wenjie YangChihua ChenYanzhao YangLei ChenChangwei YangLianggeng GongJianing WangFeng ShiDijia WuFuhua YanPublished in: La Radiologia medica (2023)
With the DL system serving as a concurrent reader, the overall post-processing and reading time was substantially reduced. The diagnostic accuracy of human readers, especially for inexperienced readers, was improved. DL-assisted human reader had the potential of being the reading mode of choice in clinical routine.
Keyphrases
- coronary artery disease
- endothelial cells
- deep learning
- coronary artery
- induced pluripotent stem cells
- working memory
- machine learning
- percutaneous coronary intervention
- magnetic resonance imaging
- left ventricular
- artificial intelligence
- atrial fibrillation
- cardiovascular events
- convolutional neural network
- risk assessment
- image quality
- climate change
- rectal cancer
- aortic stenosis
- real time pcr
- ejection fraction