Prediction of Stroke Infarct Growth Rates by Baseline Perfusion Imaging.
Anke WoutersDavid RobbenSoren ChristensenHenk A MarqueringYvo B W E M RoosRobert J van OostenbruggeWim H van ZwamDiederik W J DippelCharles B L M MajoieWouter J SchonewilleAad van der LugtMaarten LansbergGregory W AlbersPaul SuetensRobin LemmensPublished in: Stroke (2021)
We validated a deep learning-based method which improved final infarct volume estimations compared with classic computed tomography perfusion imaging processing. In addition, the deep learning model predicted individual infarct growth rates which could enable the introduction of tissue clocks during the management of acute stroke.
Keyphrases
- deep learning
- computed tomography
- high resolution
- acute myocardial infarction
- contrast enhanced
- artificial intelligence
- convolutional neural network
- atrial fibrillation
- magnetic resonance imaging
- positron emission tomography
- heart failure
- fluorescence imaging
- acute coronary syndrome
- photodynamic therapy
- percutaneous coronary intervention
- cerebral ischemia