# MR elastography datasets including phantom, liver, and brain

## TL;DR

This paper introduces MRE datasets for phantom, liver, and brain tissues to improve biomechanical property estimation in medical imaging.

## Contribution

The novel contribution is providing a benchmark phantom dataset and real human tissue data with a state-of-the-art inversion algorithm for MRE.

## Key findings

- Phantom data serves as a reliable benchmark for validating MRE inversion algorithms.
- Human liver and brain datasets demonstrate practical MRE applications in clinical scenarios.
- The TWENN algorithm is provided for comparative analysis of biomechanical parameter inversion.

## Abstract

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.