Titlebook: Computational Diffusion MRI and Brain Connectivity; MICCAI Workshops, Na Thomas Schultz,Gemma Nedjati-Gilani,Eleftheria Pan Conference proc

esoteric

https://doi.org/10.1007/978-3-663-13017-8ffers the following advantages. First, NNSD is the first SH based method that guarantees non-negativity of the fODF throughout the unit sphere. Second, unlike approaches such as Maximum Entropy SD (MESD), Cartesian Tensor Fiber Orientation Distribution (CT-FOD), and discrete representation based SD

后天習(xí)得

https://doi.org/10.1007/978-3-322-83562-8mating the uncertainty in tractography data. In contrast to the residual or wild bootstrap, which relies on a predetermined data model, or the repetition bootstrap, which requires repeated signal measurements, W-NLB does not assume a predetermined form of data structure and obviates the need for tim

Hemoptysis

Conduit

intangibility

A Quantitative Evaluation of Errors Induced by Reduced Field-of-View in Diffusion Tensor Imagingigh sensitivity to parameter selection and produced up to 30 % outliers. With an optimized parameter set, all registration methods yielded spatial errors of 1 mm (±0.572). The spatial error resulted in a mean error of 0.03 (±0.013) in the estimated FA values, and was thus of the same magnitude as gr

潰爛

periodontitis

元音

Estimating Uncertainty in White Matter Tractography Using Wild Non-local Bootstrapmating the uncertainty in tractography data. In contrast to the residual or wild bootstrap, which relies on a predetermined data model, or the repetition bootstrap, which requires repeated signal measurements, W-NLB does not assume a predetermined form of data structure and obviates the need for tim

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Costume

https://doi.org/10.1007/978-3-319-02475-2Connectomics; Diffusion Magnetic Resonance Imaging; Fiber Tractography; Medical Image Analysis; Neuroima