https://www.selleckchem.com/products/blu-451.html
PURPOSE Electrode bending observed after stereotactic interventions is typically not accounted for in either computer-assisted planning algorithms, where straight trajectories are assumed, or in quality assessment, where only metrics related to entry and target points are reported. Our aim is to provide a fully automated and validated pipeline for the prediction of stereo-electroencephalography (SEEG) electrode bending. METHODS We transform electrodes of 86 cases into a common space and compare features-based and image-based neural netw
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