Automated estimation of ischemic core volume on noncontrast-enhanced CT via machine learning.
Iris E ChenBrian TsuiHaoyue ZhangJoe X QiaoWilliam HsuMay NourNoriko SalamonLuke LedbetterJennifer PolsonCorey ArnoldMersedeh BahrHossieniReza JahanGary DuckwilerJeffrey SaverDavid LiebeskindKambiz NaelPublished in: Interventional neuroradiology : journal of peritherapeutic neuroradiology, surgical procedures and related neurosciences (2022)
The ischemic core volumes calculated by the described ML approach on NCCT approximate those obtained by MRI in patients with AIS who present beyond 1 hour from stroke onset.
Keyphrases
- machine learning
- contrast enhanced
- cerebral ischemia
- dual energy
- magnetic resonance imaging
- computed tomography
- ischemia reperfusion injury
- deep learning
- atrial fibrillation
- artificial intelligence
- blood pressure
- image quality
- big data
- high throughput
- magnetic resonance
- subarachnoid hemorrhage
- positron emission tomography
- oxidative stress