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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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Related Experiment Video

Updated: Jul 5, 2025

Quantification of Mouse Heart Left Ventricular Function, Myocardial Strain, and Hemodynamic Forces by Cardiovascular Magnetic Resonance Imaging

Quantification of Mouse Heart Left Ventricular Function, Myocardial Strain, and Hemodynamic Forces by Cardiovascular Magnetic Resonance Imaging

Published on: May 24, 2021

CMRsim-A python package for cardiovascular MR simulations incorporating complex motion and flow.

Jonathan Weine¹, Charles McGrath¹, Pietro Dirix¹

¹Institute for Biomedical Engineering, University and ETH Zurich, Zurich, Switzerland.

Magnetic Resonance in Medicine

|January 18, 2024

Summary

This summary is machine-generated.

This study introduces CMRsim, an open-source framework for cardiovascular magnetic resonance (CMR) simulations. It enables the study of complex motion and turbulent flow in CMR imaging, advancing acquisition and reconstruction techniques.

Keywords:

GPU MRI simulation Python cardiovascular motion open source

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Last Updated: Jul 5, 2025

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Area of Science:

Medical Imaging
Computational Science
Biophysics

Background:

Cardiovascular magnetic resonance (CMR) imaging is crucial for diagnosing heart conditions.
Accurate simulation of complex physiological processes like motion and flow is vital for developing advanced CMR techniques.
Existing simulation tools often lack the capability to model intricate dynamics, hindering the progress of CMR acquisition and reconstruction.

Purpose of the Study:

To introduce CMRsim, a novel open-source software framework for simulating cardiovascular magnetic resonance (CMR) images.
To enable the incorporation of complex physiological motion and turbulent flow within CMR simulations.
To facilitate the systematic study and development of advanced CMR acquisition and reconstruction strategies.

Main Methods:

CMRsim utilizes dynamic digital phantoms with complex motion as input for image simulation.
It offers two simulation paradigms: numerical and analytical solutions to the Bloch equations.
TensorFlow and GPU acceleration are employed for efficient, high-speed simulations, including turbulent flow and diffusion tensor imaging.

Main Results:

Simulations of turbulent flow in phase-contrast imaging demonstrated characteristic phase contrast and magnitude modulation, mirroring real-world data.
Cardiac diffusion tensor imaging simulations accurately reflected alterations in diffusion metrics due to strain.
The framework achieved competitive simulation speeds, with complex flow simulations taking approximately 29 minutes and diffusion imaging around 10 seconds per volume.

Conclusions:

CMRsim is the first open-source framework capable of feasibly incorporating complex motion, including turbulent flow, for advanced CMR research.
Its modular and transparent design promotes maintainability and extensibility, supporting reproducible scientific endeavors.
The tool empowers researchers to systematically investigate and refine CMR acquisition and reconstruction methods.