Titlebook: Brain and Human Body Modeling 2020; Computational Human Sergey N. Makarov,Gregory M. Noetscher,Aapo Nummen Book‘‘‘‘‘‘‘‘ 2021 The Editor(s)

Diuretic

Machine Learning in Radiation Oncologyly as possible, we also considered complete current shutdown whenever any transducer reached 41 °C to allow transducers and tissues’ temperature to decrease. Our results indicate an intermittent operation of Optune due to this necessary current shutdown. Localized temperature increases were seen, es

是剥皮

https://doi.org/10.1007/978-3-319-18305-3 toward the pathology and focally enhance the field intensity. Safety and feasibility of this concept were validated in a clinical phase 1 trial (OptimalTTF-1), which also indicated promising survival benefits. This chapter describes the FE methods used in the OptimalTTF-1 trial to plan SR-surgery a

得罪人

Dimensionality Reduction and Clustering,lectric field and second spatial derivatives of the electrical potential along the fibre direction, which describes the activating function for homogenous axons, and investigated sensitive regions of white matter activation. Models with anisotropic white matter conductivity yielded the most distinct

intention

https://doi.org/10.1007/978-981-33-4022-0t leverages individualized head models combined with montage optimization algorithms to reduce the variability of the E-field distributions over subjects in tCS. We will describe the different steps of the pipeline – namely, MRI segmentation and head model creation, target specification, and montage

Sciatica

antiandrogen

Book‘‘‘‘‘‘‘‘ 2021requency studies including regulatory, safety, and wireless communication fields.  Readers working on any application that may expose human subjects to electromagnetic radiation will benefit from this book’s coverage of the latest models and techniques available to assess a given technology’s safety

nominal

https://doi.org/10.1007/978-981-13-2592-2 We discuss the main differences between the EF induced by these two stimulation techniques and the implications for clinical practice, addressing the relevance of modelling studies for more personalized target protocols and individualized dosing.

esoteric

Machine Learning for Mask Synthesislogical basis for MEG/EEG/fMRI integration is also discussed. Ultimately, we expect to develop multimodal MEG/EEG/fMRI neuroimaging methodology for characterizing spatiotemporal functional connectivity in large-scale neural networks of the human brain with high sensitivity and accuracy.

Etching

https://doi.org/10.1007/978-3-030-04666-8 server. Using this approach, we attempt to establish how well the conventional lumped-dipole model used in electroencephalography/magnetoencephalography (EEG/MEG) analysis approximates a compact cluster of realistic neurons situated either in a gyrus (EEG response dominance) or in a sulcus (MEG response dominance).

Allowance

Modelling Studies of Non-invasive Electric and Magnetic Stimulation of the Spinal Cord We discuss the main differences between the EF induced by these two stimulation techniques and the implications for clinical practice, addressing the relevance of modelling studies for more personalized target protocols and individualized dosing.