Titlebook: Computational Diffusion MRI; International MICCAI Noemi Gyori,Jana Hutter,Fan Zhang Conference proceedings 2021 The Editor(s) (if applicabl

摻假

Expertise

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Towards Learned Optimal ,-Space Sampling in Diffusion MRIious results, the present work consolidates the above strategies into a unified estimation framework, in which the optimization is carried out with respect to both estimation model and sampling design .. The proposed solution offers substantial improvements in the quality of signal estimation as wel

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玉米

bronchodilator

Diffusion MRI Fiber Orientation Distribution Function Estimation Using Voxel-Wise Spherical U-Net the signals corresponding to individual fibers. We compared our model with another deep learning approach based on a 3D convolutional neural network and a state-of-the-art approach—multi-shell multi-tissue constrained spherical deconvolution, on real data from Human Connectome Project and synthetic

deciduous

Jubilation

DW-MRI Microstructure Model of Models Captured Via Single-Shell Bottleneck Deep Learningn to map a common basis among DW-MRI modeling approaches. We propose to capture a compact feature space in the form of a bottleneck that preserves common features to all methods and retrieve information from single shell DW-MRI. We train on 3D patches of 40 Human Connectome Project (HCP) subjects (.