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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: May 31, 2026

A Standardized Protocol for Functional Motor Mapping Using Navigated Transcranial Magnetic Stimulation

A Standardized Protocol for Functional Motor Mapping Using Navigated Transcranial Magnetic Stimulation

Published on: February 27, 2026

Self-encoded marker for optical prospective head motion correction in MRI.

Christoph Forman¹, Murat Aksoy, Joachim Hornegger

¹Department of Radiology, Stanford University, Stanford, CA, USA. Christoph.Forman@informatik.uni-erlangen.de

Medical Image Analysis

|June 29, 2011

Summary

A new self-encoded marker enhances patient motion tracking during magnetic resonance imaging (MRI). This improved method allows for accurate head pose estimation even with partial marker visibility, leading to better image quality in brain MRI scans.

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Multimodal Cross-Device and Marker-Free Co-Registration of Preclinical Imaging Modalities

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Published on: October 27, 2023

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Last Updated: May 31, 2026

A Standardized Protocol for Functional Motor Mapping Using Navigated Transcranial Magnetic Stimulation

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Published on: February 27, 2026

Multimodal Cross-Device and Marker-Free Co-Registration of Preclinical Imaging Modalities

Multimodal Cross-Device and Marker-Free Co-Registration of Preclinical Imaging Modalities

Published on: October 27, 2023

Area of Science:

Medical Imaging
Biomedical Engineering
Computer Vision

Background:

Patient motion during magnetic resonance imaging (MRI) acquisition remains a significant challenge, impacting image quality and diagnostic accuracy.
Current methods, like using checkerboard markers for head pose tracking in brain MRI, have limited tracking range due to the narrow field of view (FOV) of in-bore cameras.

Purpose of the Study:

To develop a novel self-encoded marker system for robust patient motion tracking and compensation during MRI.
To overcome the limitations of existing marker systems regarding tracking range and processing speed.

Main Methods:

A novel self-encoded marker was developed, with each feature augmented by a 2-D barcode, enabling tracking even with partial visibility.
The marker system was tested using a cylindrical phantom, demonstrating motion correction capabilities.
In vivo experiments were conducted to evaluate the performance of motion-compensated images.

Main Results:

The self-encoded marker successfully tracked motion, recovering an 18° rotation in phantom scans with high precision (0.39 mm translation, 0.15° rotation error after registration).
Motion-compensated MRI scans in subjects with significant motion showed a high correlation (0.982) with motion-free reference scans.
The novel marker significantly improved processing speed by eliminating the need for feature point correspondence searches.

Conclusions:

The developed self-encoded marker offers a superior solution for patient motion tracking and compensation in MRI compared to traditional methods.
This technology has the potential to significantly improve the quality and reliability of brain MRI and other imaging modalities affected by motion.
The system's enhanced tracking range and processing efficiency make it a promising advancement for clinical MRI applications.