External Hardware and Sensors, for Improved MRI.

Area of Science:

• Medical Imaging
• Biomedical Engineering
• Sensor Technology

Background:

• Complex engineered systems, including MRI scanners, utilize ancillary devices for monitoring.
• Some devices actively participate in the MRI image acquisition process.
• Traditional devices like electrocardiography (ECG) and respiratory bellows monitor physiological motion.

Purpose of the Study:

• To review ancillary devices that support MRI acquisitions.
• To explore the potential of diverse sensor signals in enhancing MRI.
• To discuss the integration of these devices with machine learning for improved capabilities.

Main Methods:

• Review of existing ancillary devices in clinical and research settings.
• Categorization of devices based on measured physical properties (mechanical, acoustic, optical, electromagnetic).
• Discussion of complementary signal integration and machine learning applications.

Main Results:

• A wide range of ancillary devices exist, measuring diverse physical properties.
• These devices can provide unique and complementary information to MRI acquisitions.
• No inherent competition exists between devices; they can coexist if useful and non-interfering.

Conclusions:

• Ancillary devices offer signal diversity, enriching MRI measurements.
• Future MRI acquisitions may incorporate multiple complementary signals.
• Machine learning algorithms can effectively integrate diverse inputs for enhanced MRI performance.