| Autor: |
Lavrova, Elizaveta, Kooi, Eline, wooodruff, Henry, Kassem, Mohamed, Lambin, Philippe |
| Rok vydání: |
2022 |
| Předmět: |
|
| DOI: |
10.17605/osf.io/vpt2b |
| Popis: |
Patients with symptomatic carotid artery stenosis are at high risk for recurrent stroke. To date, the decision to perform carotid endarterectomy in patients with a recent cerebrovascular event is mainly based on degree of stenosis of the ipsilateral carotid artery. However, additional atherosclerotic plaque characteristics might be better predictors of stroke, allowing for more precise selection of patients for carotid endarterectomy. The atherosclerotic plaque characteristics are typically delineated manually or with a non-deep learning method, which is time-consuming and is affected by inter- and intra-observer variability. There is an unmet clinical need for automated methods for endarterectomy patients selection with high accuracy and reproducibility. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
|
