Mode-Mixing Apparatus for MRI Signal Compression
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current MRI systems face challenges with high RF receiver channel requirements, data bus bottlenecks, and computational burdens during image reconstruction, particularly with large coil arrays, which limit scan time reduction and image quality.
Innovation Solution
A hardware-based mode-mixing system that compresses multi-channel MR signals using a mode-mixing apparatus with splitters, combiners, amplifiers, and phase shifters, reducing the number of RF receivers needed by transforming sensitivity patterns into orthogonal modes, allowing for sensitivity and encoding benefits with fewer channels.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If large coil arrays are used to improve sensitivity and encoding capability, then image quality and scan speed are improved, but the number of RF receiver channels and computational burden increase significantly
Solution Approach 1:
The patent extracts and eliminates redundant information from multi-channel coil data by identifying and removing correlated signals. The system processes the full multi-channel data to identify redundant components, then extracts only the independent signal components for reconstruction, reducing the effective number of channels needed while preserving image quality and scan speed benefits.
Solution Approach 2:
The patent discards redundant correlated signals from the multi-channel coil array data during processing, then recovers the essential independent information needed for image reconstruction. This selective discarding of redundant data reduces the computational burden and RF receiver channel requirements while maintaining the sensitivity and encoding benefits of large coil arrays.
2Measurement precision
If large coil arrays are used to improve sensitivity and encoding capability, then image quality is improved, but computational burden during reconstruction increases
Solution Approach 1:
The patent extracts only the independent signal components from the multi-channel coil data, eliminating redundant correlated information before reconstruction. This extraction process reduces the computational burden during image reconstruction while preserving the high-quality imaging benefits of large coil arrays by working only with essential independent data.
Solution Approach 2:
The patent discards redundant correlated signals during the processing stage, then recovers the essential independent information needed for high-quality image reconstruction. This approach significantly reduces computational power requirements while maintaining image quality by eliminating unnecessary computational operations on redundant data.
3Device complexity
If the number of RF receiver channels is reduced to simplify the system, then device complexity is reduced, but sensitivity and encoding capability deteriorate
Solution Approach 1:
The patent introduces a signal processing intermediary that processes the full multi-channel coil array data to identify and extract independent signal components. This intermediary processing stage allows the system to maintain the sensitivity and encoding capability benefits of large coil arrays while outputting reduced-channel data suitable for simpler reconstruction systems, effectively mediating between the physical coil array and the reconstruction algorithm.
Data Source
AI summary
The present invention provides a system and method for using a hardware-based compression of signals acquired with an magnetic resonance imaging (MRI) system. This allows a first multi-channel MR signal to be compressed to a second multi-channel MR signal having fewer channels than the first MR signal. This system and method reduces the number of RF receivers needed to achieve the sensitivity encoding benefits associated with highly parallel detection in MRI. Furthermore, the system and method reduces bottlenecks connection an MRI system's RF receiver and reconstruction computer and reduces the computational burden of image reconstruction.