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Updated: May 31, 2026

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Co-analysis of Brain Structure and Function using fMRI and Diffusion-weighted Imaging
Published on: November 8, 2012
Collaborative Reconstruction of PROPELLER-EPI Data Using POCSMUSE (CORPUSE) for High-Fidelity Diffusion MRI
Hailin Xiong1, Liyuan Liang1,2, Shihui Chen1,2
1Department of Biomedical Engineering, The Chinese University of Hong Kong, Hong Kong, China.
Magnetic Resonance in Medicine
|May 30, 2026
Summary
The CORPUSE framework enhances diffusion-tensor imaging (DTI) by improving image quality and efficiency in DW-PROPELLER-EPI scans. This novel approach allows for high-resolution DTI with fewer blades, reducing artifacts and motion sensitivity.
Area of Science:
- Magnetic Resonance Imaging (MRI)
- Diffusion Imaging
- Image Reconstruction
Background:
- Diffusion-weighted imaging (DWI) is crucial for assessing tissue microstructure.
- PROPELLER-EPI techniques improve motion robustness but face challenges with acceleration and artifacts.
- Efficient, high-resolution DWI is needed for clinical applications.
Purpose of the Study:
- Develop a reconstruction framework (CORPUSE) for multiblade DW-PROPELLER-EPI.
- Improve image quality, SNR efficiency, and reduce artifacts under acceleration.
- Enable high-resolution DTI with fewer blades.
Main Methods:
- CORPUSE is a joint reconstruction framework adapted from POCSMUSE for multiblade DW-PROPELLER-EPI.
- Integrates distortion-correction and exploits multiblade sampling redundancy.
- Uses phase errors and field maps as physics-based constraints for reconstruction.
Main Results:
- CORPUSE improved image sharpness, geometric fidelity, and reconstruction quality compared to conventional methods.
- Enabled higher per-blade acceleration and wider blades without compromising image quality.
- Demonstrated superior motion resilience compared to multiplexed sensitivity encoding (MUSE).
Conclusions:
- CORPUSE framework enables high-resolution, high-quality DTI with fewer blades.
- Improves practicality and efficiency of DW-PROPELLER-EPI.
- Offers a robust, efficient alternative to other multishot diffusion imaging approaches.
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