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Anatomy-driven multiple trajectory planning (ADMTP) of intracranial electrodes for epilepsy surgery.

, , , , , , , , , and . Int. J. Comput. Assist. Radiol. Surg., 12 (8): 1245-1255 (2017)

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Anatomy-driven multiple trajectory planning (ADMTP) of intracranial electrodes for epilepsy surgery., , , , , , , , , and . Int. J. Comput. Assist. Radiol. Surg., 12 (8): 1245-1255 (2017)Towards Uncertainty Quantification for Electrode Bending Prediction in Stereotactic Neurosurgery., , , , , , , , , and . ISBI, page 674-677. IEEE, (2020)Machine learning to detect brain lesions in focal epilepsy., , , , , and . Medical Imaging: Image-Guided Procedures, volume 11598 of SPIE Proceedings, SPIE, (2021)A Machine Learning Approach to Predict Instrument Bending in Stereotactic Neurosurgery., , , , , , , , , and 1 other author(s). MICCAI (4), volume 11073 of Lecture Notes in Computer Science, page 238-246. Springer, (2018)Recursive calibration of the fiber response function for spherical deconvolution of diffusion MRI data., , , , and . NeuroImage, (2014)Tractography dissection variability: What happens when 42 groups dissect 14 white matter bundles on the same dataset?, , , , , , , , , and 131 other author(s). NeuroImage, (2021)Independent components of human brain morphology., , , , , , , , , and 1 other author(s). NeuroImage, (2021)Automatic segmentation of stereoelectroencephalography (SEEG) electrodes post-implantation considering bending., , , , , , , , , and 4 other author(s). Int. J. Comput. Assist. Radiol. Surg., 13 (6): 935-946 (2018)Using convolution neural networks to learn enhanced fiber orientation distribution models from commercially available diffusion magnetic resonance imaging., , , , , , and . CoRR, (2020)Automated longitudinal intra-subject analysis (ALISA) for diffusion MRI tractography., , , , , and . NeuroImage, (2014)