Detecting CTP truncation artifacts in acute stroke imaging from the arterial input and the vascular output functions

Keyphrases

• Output Function 100%
• CT Perfusion 100%
• Truncation Artifact 100%
• Acute Stroke Imaging 100%
• Precision-recall 80%
• ROC-AUC 80%
• F1 Score 80%
• Scan Duration 80%
• Arterial Input Function 80%
• Lesion Volume 60%
• Truncation 40%
• Machine Learning Models 40%
• Short Scan 40%
• Perfusion Analysis 40%
• Baseline Classifiers 40%
• Perfusion 20%
• Machine Learning 20%
• Clinical Practice 20%
• Function-based 20%
• Automatic Method 20%
• Clinical Standards 20%
• 5-fold Cross Validation 20%
• Perfusion Time 20%
• Current Guidelines 20%
• Acute Stroke 20%
• Predictive Features 20%
• Truncated Series 20%
• Acquisition Duration 20%
• Stroke Lesion 20%
• Feature Classifier 20%
• Lesion Measurement 20%
• Single Feature 20%
• Function Features 20%
• Background Current 20%

Computer Science

• Output Function 100%
• Input Function 100%
• Machine Learning Model 50%
• Interpretability 25%
• Fold Cross Validation 25%
• Single Feature 25%
• Time Difference 25%
• Machine Learning 25%
• Learning System 25%

Neuroscience

• Cerebrovascular Accident 100%