Keywords: Stroke, Machine Learning/Artificial Intelligence, Large vessel occlusion, TOF, MR angiographyLarge vessel occlusion (LVO) in stroke patients is mostly detected using deep-learning-based automated methods on CT angiography but there has been no report on such methods using time-of-flight magnetic resonance angiography (TOF-MRA). Our study includes 460 stroke patients with 230 LVO-positive cases. The first step was vessel segmentation, and the output mask was used for the LVO detection. Both steps were deep-learning based using TOF-MRA. Our model successfully detected 95% LVO-positive and 92% LVO-negative patients. The high detection rate and short processing time (< 60 seconds) suggested that our model is highly adequate in a clinical emergency context.
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