Adaptive Channel Reduction for Parallel MRI Imaging
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Solution Overview
Problem
Parallel imaging methods in MRI face challenges with increased system load and reconstruction time due to the number of channels, leading to significant information loss when channels are reduced for faster processing.
Innovation Solution
The method involves adaptive channel reduction by selecting and combining RF coil signals using sensitivity maps and combiner matrices, such as PCA or SVD, to create fewer output channels that maintain image quality and reduce resource usage during reconstruction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If more RF array channels are added to improve image signal-to-noise ratio, then image quality is improved, but system load increases greater than linearly and reconstruction time increases
Solution Approach 1:
The patent implements dynamic channel selection where the system adapts the number and configuration of active channels based on the specific imaging task, field of view, and anatomical region. Rather than using a fixed channel configuration, the system dynamically reconfigures which channels are active and how they are combined, allowing optimization between SNR and reconstruction speed for different scenarios.
Solution Approach 2:
The patent changes the parameter of effective channel count by using channel compression techniques. Instead of always using all available channels, the system compresses the channel data into fewer effective channels while preserving the necessary imaging information. This parameter change allows the system to maintain image quality while reducing the computational burden associated with processing all original channels.
2Productivity
If channel compression is applied to reduce system load and reconstruction time, then processing speed is improved, but significant information can be lost when channels are turned off
Solution Approach 1:
The patent performs preliminary channel compression and mode selection before the actual imaging reconstruction process. By pre-determining which channels to activate and how to combine them based on the imaging task requirements, the system prepares optimized channel configurations in advance. This preliminary action ensures that when reconstruction occurs, the necessary information has already been preserved in the compressed channel representation.
Solution Approach 2:
The system incorporates feedback mechanisms to monitor and evaluate the quality of reconstructed images and adjust channel compression parameters accordingly. By analyzing the reconstruction quality and comparing it against the original full-channel results, the system can fine-tune the compression level to maintain acceptable information fidelity while maximizing speed benefits.
3Device complexity
If channel sub-selection is used to reduce reconstruction load, then system resources are reduced, but for large field of view images significant information is lost
Solution Approach 1:
The patent applies local quality optimization by selecting and combining channels based on their spatial sensitivity characteristics. Different channels are weighted and combined differently depending on their spatial coverage and sensitivity profiles. This local optimization ensures that channels providing the most useful information for the specific field of view are prioritized, reducing information loss while managing reconstruction complexity.
Solution Approach 2:
The patent creates a universal channel compression framework that can adapt to different imaging scenarios, field of views, and anatomical regions. The same basic compression architecture can serve multiple purposes by dynamically adjusting which channels are active and how they are combined. This multi-functionality allows the system to handle both small and large field of view images effectively without requiring separate specialized systems.
Data Source
AI summary
The subject invention pertains to method and apparatus for parallel imaging. The subject method can be utilized with imaging systems utilizing parallel imaging techniques. In a specific embodiment, the subject invention can be used in magnetic resonance imaging (MRI). A specific embodiment of the subject invention can reduce parallel reconstruction CPU and system resources usage by reducing the number of channels employed in the parallel reconstruction from the M channel signals to a lower number of channel signals. In a specific embodiment, sensitivity map information can be used in the selection of the M channel signals to be used, and how the selected channel signals are to be combined, to create the output channel signals. In an embodiment, for a given set of radio-frequency (RF) elements, an optimal choice of reconstructed channel modes can be made using prior view information and/or sensitivity data for the given slice. The subject invention can utilize parallel imaging speed up in multiple directions.