2024
DOI: 10.1088/1361-6560/ad45a5
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FlexDTI: flexible diffusion gradient encoding scheme-based highly efficient diffusion tensor imaging using deep learning

Zejun Wu,
Jiechao Wang,
Zunquan Chen
et al.

Abstract: Objective:
Most deep neural network-based diffusion tensor imaging methods require the diffusion gradients' number and directions in the data to be reconstructed to match those in the training data. This work aims to develop and evaluate a novel dynamic-convolution-based method called FlexDTI for highly efficient diffusion tensor reconstruction with flexible diffusion encoding gradient scheme.
Approach:
FlexDTI was developed to achieve high-quality DTI parametric mapping with flexible n… Show more

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