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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: Jan 7, 2026

Registered Bioimaging of Nanomaterials for Diagnostic and Therapeutic Monitoring

Registered Bioimaging of Nanomaterials for Diagnostic and Therapeutic Monitoring

Published on: December 9, 2010

Microscopic Propagator Imaging with diffusion MRI.

Tommaso Zajac¹, Gloria Menegaz¹, Marco Pizzolato²

¹Department of Engineering for Innovation Medicine, University of Verona, Verona, Italy.

Magnetic Resonance Imaging

|December 31, 2025

Summary

This summary is machine-generated.

Microscopic Propagator Imaging (MPI) is a new diffusion MRI method. It provides detailed maps of brain tissue microstructure, offering insights beyond traditional techniques.

Keywords:

Diffusion MRI Ensemble Average Propagator Spherical harmonics Zonal modeling

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Last Updated: Jan 7, 2026

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Diffusion Imaging in the Rat Cervical Spinal Cord

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Published on: April 7, 2015

Area of Science:

Neuroimaging
Biophysics
Machine Learning

Background:

Diffusion MRI measures water diffusion in tissue.
Conventional methods are sensitive to tissue microstructure and orientation.
Microscopic Propagator Imaging (MPI) aims to isolate microstructural properties.

Purpose of the Study:

Introduce and validate Microscopic Propagator Imaging (MPI).
Assess MPI's ability to characterize brain tissue microstructure.
Compare MPI with conventional diffusion MRI methods.

Main Methods:

MPI utilizes a machine learning framework.
It analyzes multi-shell diffusion MRI data using spherical harmonic coefficients.
The method maps diffusion data to microscopic propagator indices.

Main Results:

MPI provides reliable voxelwise estimates in human brain data.
Resulting maps show distinct spatial patterns compared to conventional methods.
MPI indices demonstrate systematic differences from mean apparent propagator indices.

Conclusions:

MPI offers microscopic-specific information complementary to classical methods.
The technique can potentially improve brain tissue microstructure characterization.
MPI shows promise for enhanced diagnostic capabilities in neuroimaging.