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Predicting Final Extent of Ischemic Infarction Using Artificial Neural Network Analysis of Multi-Parametric MRI in Patients with Stroke
2011
PLoS ONE
In hemispheric ischemic stroke, the final size of the ischemic lesion is the most important correlate of clinical functional outcome. Using a set of acute-phase MR images (Diffusion-weighted -DWI, T 1 -weighted -T1WI, T 2 -weighted-T2WI, and proton density weighted -PDWI) for inputs, and the chronic T2WI at 3 months as an outcome measure, an Artificial Neural Network (ANN) was trained to predict the 3-month outcome in the form of a voxel-by-voxel forecast of the chronic T2WI. The ANN was
doi:10.1371/journal.pone.0022626
pmid:21853039
pmcid:PMC3154199
fatcat:cmdvcptbmfhgbfgnwpmx7gs4ei