aceImproved diffusion tensor parametric maps in the brain from reduced-direction acquisitions using a deep learning approach
Objectives This study implements and evaluates a deep learning approach to enhance FA, MD, AD, and RD maps derived from 16-direction DTI to approximate corresponding maps derived from 32-direction DTI, with the aim of reducing acquisition time while maintaining quantitative accuracy. Materials and methods A modified 8-layer 3D convolutional neural network was trained using scalar DTI-derived maps from 16-direction acquisitions as input and corresponding 32-direction maps as reference targets. Model performance w…
A 3D convolutional network improved noisy scalar maps from 16-direction diffusion MRI so they agree more closely with 32-direction reference maps, cutting acquisition time about 1.8-fold.
The authors state that remaining quantitative differences and generalizability require further validation, so the approach is not yet shown to fully match 32-direction maps.
Evidence
- Peer-reviewedMagnetic Resonance Materials in Physics, Biology and Medicine2026-10-15
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Truvace Impact Record TRV-2026-1983, v1: “Improved diffusion tensor parametric maps in the brain from reduced-direction acquisitions using a deep learning approach.” Truvace, 2026-10-20. /record/TRV-2026-1983 (accessed at citation time). sha256 ab2e7638d0bee766…
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