MRF Dictionary Inner Product Approximation for Reduced Storage
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Solution Overview
Problem
Conventional magnetic resonance fingerprinting (MRF) dictionaries are excessively large, leading to significant constraints on computational and storage resources, making the process of generating tissue property maps highly resource-intensive.
Innovation Solution
The system and method approximate the inner product as a quadratic function of MRF products, reducing the size of the MRF dictionary and corresponding computational resources, allowing for efficient tissue property mapping by comparing signal evolutions to a reduced dictionary.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional MRF dictionaries are used to ensure accurate tissue property characterization, then measurement precision is improved, but device complexity and computational resources increase significantly
Solution Approach 1:
The patent segments the tissue property space into discrete grids of T1 and T2 values, creating a structured dictionary where each entry represents a specific tissue property combination. This segmentation allows the system to cover the full range of possible tissue properties while maintaining an organized, manageable structure that can be efficiently searched and processed.
Solution Approach 2:
The patent systematically varies the tissue property parameters (T1 and T2 relaxation times) across the dictionary, creating entries that represent different tissue states. By changing these parameters in a controlled manner across the dictionary grid, the system captures the full range of tissue variability while maintaining a structured format that optimizes both accuracy and computational efficiency.
2Measurement precision
If larger MRF dictionaries are used to reduce discretization errors, then measurement precision is improved, but loss of time increases due to longer processing durations
Solution Approach 1:
The patent performs preliminary generation of the MRF dictionary with fine discretization before the actual tissue property mapping process. By pre-computing the dictionary with high resolution (fine T1 and T2 steps) and storing it for reuse, the system eliminates the need to recalculate these values during each scanning session, thereby achieving high measurement precision without incurring excessive processing time during clinical use.
3Measurement precision
If fine discretization steps are used in T1 and T2 values, then measurement precision is improved, but device complexity and storage requirements increase
Solution Approach 1:
The patent segments the continuous T1 and T2 parameter spaces into discrete grids with fine steps (e.g., T1 steps of 10-50ms, T2 steps of 5-10ms). This segmentation creates a manageable set of discrete tissue property combinations that capture the essential variability of tissue properties while avoiding the infinite complexity of continuous parameters, thereby balancing precision with storage feasibility.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach results in improved efficiency and accuracy of tissue property mapping, reducing discrepancies between coarse and fine dictionary matches, and providing faster processing times compared to traditional MRF methods.
Implementation Method 1
a magnetic gradient system including a plurality of magnetic gradient coils configured to apply at least one magnetic gradient field to the polarizing magnetic field
Implementation Method 2
Magnetic resonance fingerprinting ('MRF') is a technology, which is described, as one example, by D. Ma, et al., in 'Magnetic Resonance Fingerprinting,' Nature, 2013; 495(7440):187-192, that allows one to characterize tissue species using nuclear magnetic resonance ('NMR')
Data Source
AI summary
A system and method is provided for improved magnetic resonance fingerprinting (MRF) data dictionary matching using an MRF dictionary having entries with an inner product storing tissue properties.