Deep Learning Applications in Imaging of Acute Ischemic Stroke: A Systematic Review and Narrative Summary
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View abstract on PubMed
Summary
This summary is machine-generated.Deep learning enhances acute ischemic stroke (AIS) imaging, excelling in lesion segmentation. Further research needs standardized data and real-world validation for AI in stroke care.
Area Of Science
- Medical Imaging
- Artificial Intelligence
- Neurology
Background
- Acute ischemic stroke (AIS) poses significant health risks, necessitating rapid neuroimaging analysis.
- Deep learning (DL) models show promise in advancing stroke imaging interpretation.
Conclusions
- DL is significantly impacting AIS imaging, particularly for lesion segmentation.
- Key challenges include standardizing protocols, creating larger public datasets, and validating performance in clinical settings.
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