掺假
发表于 2025-3-25 05:23:02
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Expertise
发表于 2025-3-25 09:16:53
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Parameter
发表于 2025-3-25 15:43:32
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
Infant
发表于 2025-3-25 16:31:09
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CYN
发表于 2025-3-25 21:13:29
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optional
发表于 2025-3-26 00:35:17
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玉米
发表于 2025-3-26 07:02:08
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bronchodilator
发表于 2025-3-26 11:17:04
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
发表于 2025-3-26 12:46:33
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Jubilation
发表于 2025-3-26 18:10:10
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 (.