Neural Network-derived Perfusion Maps for the Assessment of Lesions in Patients with Acute Ischemic Stroke.
Raphael MeierPaula LuxB MedSimon JungUrs FischerGralla JanMauricio ReyesRoland WiestRichard McKinleyJohannes KaesmacherPublished in: Radiology. Artificial intelligence (2019)
Compared with standard deconvolution-based processing of raw perfusion data, automatic CNN-derived Tmax perfusion maps can be applied to patients who have acute ischemic large vessel occlusion stroke, with similar clinical utility.© RSNA, 2019Supplemental material is available for this article.
Keyphrases
- neural network
- acute ischemic stroke
- end stage renal disease
- contrast enhanced
- ejection fraction
- newly diagnosed
- chronic kidney disease
- liver failure
- machine learning
- magnetic resonance imaging
- prognostic factors
- peritoneal dialysis
- ischemia reperfusion injury
- magnetic resonance
- patient reported outcomes
- intensive care unit
- drug induced
- big data
- cerebral ischemia
- computed tomography
- brain injury
- blood brain barrier
- hepatitis b virus
- aortic dissection