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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: Jun 8, 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, California, USA.

Medical Image Computing and Computer-Assisted Intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention

|October 1, 2010

Summary

A new self-encoded marker enhances magnetic resonance imaging (MRI) by enabling robust patient motion tracking. This improves image quality and accuracy, even with partial marker visibility.

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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

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Last Updated: Jun 8, 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 checkerboard markers, have limited tracking range due to the need for full marker visibility within the camera's field of view (FOV).

Purpose of the Study:

To develop and evaluate a novel self-encoded marker for improved patient motion tracking and compensation in MRI.
To overcome the FOV limitations of existing marker-based tracking systems.

Main Methods:

Development of a self-encoded marker with integrated 2-D barcodes on each feature.
Utilizing the marker for patient head pose tracking with an in-bore camera.
Implementing motion correction algorithms based on the novel marker's pose estimation.
Validation using a cylindrical phantom and in-vivo experiments.

Main Results:

The novel marker allows tracking even when not fully visible, overcoming FOV limitations.
Motion correction successfully recovered 18 degrees of rotation in phantom experiments.
Post-registration errors were minimal (0.39 mm translation, 0.15 degrees rotation).
In-vivo scans with significant motion showed high correlation (0.982) with motion-free references.

Conclusions:

The self-encoded marker offers a significant advancement in patient motion tracking for MRI.
It provides faster processing and a wider tracking range compared to traditional methods.
This technology has the potential to substantially improve the reliability and accuracy of MRI scans.