MRI Diffusion Data Acquisition Merging Multiple Models
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Solution Overview
Problem
Current diffusion imaging methods in MRI require longer acquisition times due to the need for different data acquisition methods for various diffusion models, making it inadequate for clinical research where comprehensive analysis is needed efficiently.
Innovation Solution
A diffusion model data acquisition method that combines multiple individual data sets into a single combined data set, allowing multiple diffusion models to share data, with specific shells and gradient directions optimized to reduce acquisition time while maintaining reconstruction accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If separate data acquisition methods are used for each diffusion model, then each model can be accurately reconstructed, but the overall acquisition time increases significantly
Solution Approach 1:
The patent combines multiple individual data sets corresponding to different diffusion models into a single combined data set. This merging allows all diffusion models to share the same acquired data, eliminating the need for separate acquisitions for each model while maintaining the ability to reconstruct each model accurately.
Solution Approach 2:
The combined data set serves multiple functions by supporting reconstruction for different diffusion models simultaneously. The data acquisition method is designed to be universal, where a single acquisition protocol can provide sufficient information for various diffusion model reconstructions, making the system multi-functional rather than requiring separate specialized acquisitions.
2Adaptability or versatility
If multiple individual data sets are acquired for different diffusion models, then comprehensive data coverage is achieved, but the data acquisition complexity increases
Solution Approach 1:
The patent merges multiple individual data sets into one combined data set that provides comprehensive coverage for different diffusion models. This consolidation reduces the operational complexity of managing and acquiring separate data sets while maintaining the versatility needed for various model reconstructions.
Solution Approach 2:
The combined data set is designed with universal applicability, where a single data acquisition protocol can support multiple diffusion models. This universality simplifies the acquisition process by providing a unified approach rather than requiring model-specific procedures, thereby reducing device and operational complexity.
Data Source
AI summary
In a method for acquiring MR diffusion data, in a control computer of an MRI system, multiple individual data sets, respectively corresponding to multiple diffusion models, are defined and combined to form a combined data set. Each of said individual data sets is comprised of multiple diffusion image individual data subsets that are to be acquired on one or more specific shells, respectively, and in one or more gradient directions, respectively. Different specific shells among the multiple shells have different diffusion factors. The control computer then operates the MRI system, namely the data acquisition scanner thereof, in order to acquire MR data corresponding to the defined combined data set.