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DTDMapper

DTDMapper is a deep learning–based framework designed to accelerate diffusion tensor distribution (DTD) mapping. By leveraging a Transformer architecture, it directly predicts voxel-wise DTD-derived parameters from diffusion MRI signals, achieving fast and accurate microstructural characterization compared with conventional Monte Carlo inversion

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DTDMapper is a deep learning–based framework designed to accelerate diffusion tensor distribution (DTD) mapping. By leveraging a Transformer architecture, it directly predicts voxel-wise DTD-derived parameters from diffusion MRI signals, achieving fast and accurate microstructural characterization compared with conventional Monte Carlo inversion

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