Neuroscience
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Multicenter Study
Deep learning-based segmentation of acute ischemic stroke MRI lesions and recurrence prediction within 1 year after discharge: A multicenter study.
To explore the performance of deep learning-based segmentation of infarcted lesions in the brain magnetic resonance imaging (MRI) of patients with acute ischemic stroke (AIS) and the recurrence prediction value of radiomics within 1 year after discharge as well as to develop a model incorporating radiomics features and clinical factors to accurately predict AIS recurrence. ⋯ The MRA-UNet model can effectively improve the segmentation accuracy of MRI. The model, which was established by combining radiomics features and clinical factors, held some value for predicting AIS recurrence within 1 year.