Machine learning-based segmentation of ischemic penumbra by using diffusion tensor metrics in a rat model
Background Recent trials have shown promise in intra-arterial thrombectomy after the first 6–24 h of stroke onset. Quick and precise identification of the salvageable tissue is essential for successful stroke management. In this study, we examined the feasibility of machine learning (ML) approaches...
| Main Authors: | , , , , , , |
|---|---|
| Other Authors: | |
| Format: | Article |
| Language: | English |
| Published: |
BioMed Central
2021
|
| Online Access: | https://hdl.handle.net/1721.1/131575 |