Auxiliary Sensor Noise Suppression for Low-Field MRI Systems
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
High-field MRI systems are limited by their high cost and size, making them unavailable for widespread clinical use, while low-field systems lack the image quality for clinical applications due to noise interference in unshielded environments.
Innovation Solution
Developing noise suppression techniques using auxiliary sensors and transforms to estimate and subtract noise from MR signals in low-field MRI systems, allowing them to operate effectively in unshielded environments and improving image quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If low-field MRI systems are used, then cost and size are reduced, but image quality deteriorates due to noise interference
Solution Approach 1:
An auxiliary sensor is introduced as an intermediary device to detect environmental noise separately from the primary coil. The auxiliary sensor captures noise signals that are then used to generate correction data, which serves as a mediator to remove noise from the MR signal without requiring extensive shielding infrastructure
Solution Approach 2:
The noise component is extracted from the MR signal through a multi-step process: the auxiliary sensor extracts environmental noise, the transform estimates noise present in the primary coil signal, and this estimated noise is then subtracted from the original MR signal to produce a cleaned signal with improved image quality
2Measurement precision
If high-field MRI systems are used, then image quality is improved, but cost and availability worsen
Solution Approach 1:
The system changes the operating parameters of the low-field MRI by dynamically adjusting the frequency band or bin based on noise measurements from the auxiliary sensor. This allows the system to operate effectively at lower field strengths by adapting to environmental noise conditions rather than requiring the high field strength traditionally needed for quality imaging
3Object-affected harmful factors
If extensive shielding is implemented, then noise is reduced, but system complexity and cost increase
Solution Approach 1:
The patent replaces the mechanical/physical shielding infrastructure with an electronic/software-based noise suppression system. Instead of using physical barriers to block noise, the system uses auxiliary sensors to detect noise and computational transforms to estimate and remove noise from the MR signal, eliminating the need for extensive electromagnetic shielding
Data Source
AI summary
Techniques for suppressing noise in an environment of a magnetic resonance (MR) imaging system having at least one primary coil and at least one auxiliary sensor. The techniques involve estimating a transform, that, when applied to noise received by the at least one auxiliary sensor, provides an estimate of noise received by the at least one primary coil. The transform is estimated from data obtained by the at least one primary coil and the least one auxiliary sensor, with the data being weighted prior to estimation to remove or suppress data in regions with a high signal to noise ratio. In turn, the estimated transform may be applied to noise measured by the at least one auxiliary sensor during imaging of a patient, to estimate and suppress noise present in the MR signals received by the at least one primary coil during imaging.