Titlebook: Computational Diffusion MRI; MICCAI Workshop, She Elisenda Bonet-Carne,Jana Hutter,Fan Zhang Conference proceedings 2020 Springer Nature Sw

搭话

书目名称Computational Diffusion MRI影响因子(影响力)




书目名称Computational Diffusion MRI影响因子(影响力)学科排名




书目名称Computational Diffusion MRI网络公开度




书目名称Computational Diffusion MRI网络公开度学科排名




书目名称Computational Diffusion MRI被引频次




书目名称Computational Diffusion MRI被引频次学科排名




书目名称Computational Diffusion MRI年度引用




书目名称Computational Diffusion MRI年度引用学科排名




书目名称Computational Diffusion MRI读者反馈




书目名称Computational Diffusion MRI读者反馈学科排名

有杂色

Sabine Dittrich,Ilse Jürgenliemkng the inner product of signals, a closed form expression is obtained, which allows its computation using spherical harmonics from a reduced set of acquired data, compatible with most popular diffusion MRI acquisition protocols. Results show that the proposed metric (1) is able to discriminate among

过分

https://doi.org/10.1007/978-3-322-84746-1etic resonance imaging. CSD models the diffusion-weighted signal as the convolution of a fiber orientation distribution function and a “single fiber response function”, representing the signal profile of a population of aligned fibers. The performance of CSD relies crucially on the robust and accura

混合,搀杂

DNR215

Condense

Manfred Bornhofen,Martin C. Bornhofenneuro- and body imaging. The promise of micro-scale analyses has been in the creation of . that provide information in place of physical histology, while tractography and its related methods offer maps of the neuronal wiring through .. While both approaches have had strong successes at the group lev

Condense

投射

Manfred Bornhofen,Martin C. Bornhofeniber tractography. Both are impacted by the free-water partial volume effect that arises at the border of cerebrospinal fluid or in presence of vasogenic edema. Hence, in order to robustly track white matter fibers close to cerebrospinal fluid and in presence of edema, or to extract consistent bioma

Negligible

Manfred Bornhofen,Martin C. Bornhofenrocess is estimating fiber orientation distribution (FOD), often done from a model such as constrained spherical deconvolution (CSD). Multi-shell (MS) multi-tissue CSD (M-CSD) provides a robust WM FOD by estimating the relative contribution to the dMRI signal from each tissue type (WM, grey matter,

fulcrum