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Magnetic Resonance Imaging

Magnetic Resonance Imaging

Magnetic resonance imaging (MRI) is a noninvasive medical imaging technique based on a phenomenon of nuclear physics discovered in the 1930s, in which matter exposed to magnetic fields and radio waves was found to emit radio signals. In 1970, a physician and researcher named Raymond Damadian noticed that malignant (cancerous) tissue gave off different signals than normal body tissue. He applied for a patent for the first MRI scanning device in clinical use by the early 1980s. The early MRI...

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Updated: Sep 29, 2025

Magnetic Resonance Elastography Methodology for the Evaluation of Tissue Engineered Construct Growth

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Published on: February 9, 2012

Multiple motion encoding in phase-contrast MRI: A general theory and application to elastography imaging.

Helge Herthum¹, Hugo Carrillo², Axel Osses³

¹Institute of Medical Informatics, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universitt zu Berlin, and Berlin Institute of Health, Berlin, 10117, Germany.

Medical Image Analysis

|March 25, 2022

Summary

We developed an Optimal Multiple Motion Encoding (OMME) method to improve Magnetic Resonance Elastography (MRE) imaging. OMME enhances motion-to-noise ratio and image detail by effectively unwrapping phase data, outperforming conventional techniques.

Keywords:

Magnetic resonance elastography Multiple motion encoding Phase-contrast MRI

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Last Updated: Sep 29, 2025

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Phase Contrast Magnetic Resonance Imaging in the Rat Common Carotid Artery

Phase Contrast Magnetic Resonance Imaging in the Rat Common Carotid Artery

Published on: September 5, 2018

Area of Science:

Medical Imaging
Biophysics
Signal Processing

Background:

Magnetic Resonance Imaging (MRI) encodes tissue motion in magnetization phase.
Phase wrapping in high-efficiency encoding limits motion image fidelity.
Magnetic Resonance Elastography (MRE) requires accurate motion estimation for stiffness mapping.

Purpose of the Study:

To introduce and validate the Optimal Multiple Motion Encoding (OMME) method.
To improve motion quantification in MRE by addressing phase wrapping.
To enhance the resolution and accuracy of MRE-derived stiffness maps.

Main Methods:

Formulated OMME as a non-convex least-squares problem for motion estimation.
Utilized an arbitrary number of phase-contrast measurements with varying motion encoding gradients (MEGs).
Assessed OMME performance on in vivo human brain MRE data and synthetic datasets.

Main Results:

OMME successfully combined multiple MRE phase images with different MEGs.
Outperformed dual encoding strategies in motion-to-noise ratio (MNR) and voxel reconstruction.
Generated stiffness maps with superior detail resolution compared to conventional unwrapping methods.
Demonstrated increased dynamic range and noise robustness for wrap-free phase images.

Conclusions:

OMME offers a flexible and robust approach to increase dynamic range and improve MRE image quality.
The method provides wrap-free phase images with high MNR, crucial for detailed stiffness reconstruction.
OMME is particularly beneficial for MRE applications demanding high-resolution, high-MNR images.