Related Experiment Video
Updated: Aug 21, 2026
Diffusion Imaging in the Rat Cervical Spinal Cord
Published on: April 7, 2015
Memory-efficient image reconstruction using diffusion models for accelerated 3D non-Cartesian UTE imaging
Jonas Petersen1,2, Stefan Sommer3,4, Thomas Küstner5
1Medical Image and Data Analysis (MIDAS.lab), Department of Diagnostic and Interventional Radiology, University of Tübingen, Tübingen, Germany. Jonas.petersen@siemens-healthineers.com.
Purpose:
Accelerated 3D non-Cartesian MRI presents unique challenges in balancing high-resolution reconstruction with computational and memory constraints. In this work, a novel, memory-efficient image reconstruction framework using score-based diffusion models tailored for highly undersampled 3D radial UTE acquisitions is proposed.
Methods:
The method leverages a volumetric extension of the NCSN++ architecture with efficient NUFFT operations and integrates a conjugate gradient-based data consistency mechanism within a predictor-corrector sampling scheme.
Results:
This approach enables robust and high-fidelity reconstructions from as few as 4000 spokes-representing up to 50 × undersampling relative to Nyquist. Generalizable performance across knee, ankle, and out-of-distribution shoulder datasets is demonstrated and superior image quality compared to compressed sensing and conventional iterative methods, especially at high acceleration factors is shown.
Conclusion:
The proposed framework marks a significant step toward practical deployment of diffusion models in non-Cartesian MRI reconstruction.
