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Author Spotlight: Advancing Hepatic Fibrosis Diagnosis Using Magnetic Resonance Elastography and AI
Published on: July 21, 2023
MR elastography datasets including phantom, liver, and brain
Yuan Feng1,2,3, Suhao Qiu4,5,6, Runke Wang4,5,6
1School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, 200030, China. fengyuan@sjtu.edu.cn.
None:
The in vivo characterization of biomechanical properties in soft biological tissues offers critical insights for both scientific research and clinical diagnostics. Magnetic resonance elastography (MRE) is a noninvasive technique that enables 3D measurements of the biomechanical properties of various soft tissues. While numerous inversion algorithms have been developed based on wave fields from MRE, robust and multi-parameter estimation of biomechanical properties remains an area of active development. Here we present comprehensive MRE datasets, including phantom, human liver, and human brain data. The phantom data serves as a benchmark for validation, while the liver and brain datasets represent typical application scenarios for MRE. All wave images were acquired using 3 T scanners, ensuring high-quality data. Additionally, a state-of-the-art inversion algorithm, the Traveling Wave Expansion-Based Neural Network (TWENN), is also provided for comparative analysis. These datasets provide a diverse range of application scenarios, facilitating the development and refinement of MRE inversion algorithms. By making these resources available, we aim to advance the field of MRE research and improve the inversion of biomechanical parameters.
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