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Real-time 4D MRI reconstruction using DVR-NeMF, a framework for dynamic volumetric reconstruction.
Ruoxi Wang1, Sijie Zhong1, Jincheng Li1
1School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China.
Cell Reports Methods
|November 21, 2025
Summary
DVR-NeMF enables real-time, 4D MRI reconstruction using neural networks. This advanced framework achieves high accuracy and efficiency, outperforming existing methods for dynamic cardiac imaging.
Area of Science:
- Medical Imaging
- Artificial Intelligence
- Biomedical Engineering
Background:
- Dynamic magnetic resonance imaging (MRI) is crucial for assessing cardiac function.
- Current MRI reconstruction methods face challenges in achieving real-time, high-dimensional imaging with anatomical fidelity.
Purpose of the Study:
- To develop a novel framework, DVR-NeMF, for real-time, 4D MRI reconstruction.
- To improve the accuracy and computational efficiency of dynamic cardiac MRI.
- To enable reliable, real-time functional assessment in clinical settings.
Main Methods:
- Developed four dynamic MRI sequences for data acquisition.
- Introduced DVR-NeMF, a neural magnetic field framework integrating spatiotemporal priors into implicit representations.
- Utilized synchronized dynamic 2D image slices and physiological signals for reconstruction.
Main Results:
- DVR-NeMF demonstrated superior reconstruction accuracy and computational efficiency compared to autoencoder and GAN baselines.
- Validated performance across cardiovascular phantoms, bio-simulators, and human hearts, including the ACDC dataset.
- Confirmed reliability through comparative analysis with cardiac ultrasound data for left ventricular function parameters.
Conclusions:
- DVR-NeMF offers a promising paradigm for dynamic, high-dimensional MRI.
- The framework enables real-time functional assessment with high anatomical fidelity.
- This advancement has significant potential for clinical applications in cardiac imaging.
