Deep learning algorithm for detection of aortic dissection on non-contrast-enhanced CT.
Akinori HataMasahiro YanagawaKazuki YamagataYuuki SuzukiShoji KidoAtsushi KawataShuhei DoiYuriko YoshidaTomo MiyataMitsuko TsubamotoNoriko KikuchiNoriyuki TomiyamaPublished in: European radiology (2020)
• A deep learning-based algorithm for detecting aortic dissection was developed using the non-contrast-enhanced CT images of 170 patients. • The algorithm had an AUC of 0.940 for detecting aortic dissection. • The accuracy, sensitivity, and specificity of the algorithm were comparable to those of radiologists.
Keyphrases
- aortic dissection
- contrast enhanced
- deep learning
- diffusion weighted
- magnetic resonance imaging
- artificial intelligence
- computed tomography
- magnetic resonance
- convolutional neural network
- machine learning
- diffusion weighted imaging
- dual energy
- end stage renal disease
- newly diagnosed
- ejection fraction
- peritoneal dialysis
- prognostic factors
- label free
- image quality