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Updated: Dec 26, 2025

Co-analysis of Brain Structure and Function using fMRI and Diffusion-weighted Imaging

Co-analysis of Brain Structure and Function using fMRI and Diffusion-weighted Imaging

Published on: November 8, 2012

Reconstructing High-Quality Diffusion MRI Data from Orthogonal Slice-Undersampled Data Using Graph Convolutional

Yoonmi Hong¹, Geng Chen¹, Pew-Thian Yap¹

¹Department of Radiology and BRIC, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.

Medical Image Computing and Computer-Assisted Intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention

|March 13, 2020

Summary

This summary is machine-generated.

This study introduces a super-resolution reconstruction method for accelerating diffusion MRI (dMRI) acquisition by undersampling slices. The technique uses graph convolutional neural networks to reconstruct full diffusion-weighted volumes, achieving up to 5x acceleration with minimal data loss.

Failed At:

2026-06-19T13:47:51.394216+00:00

Keywords:

Accelerated acquisition Adversarial learning Diffusion MRI Graph CNN Super resolution

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