B-Value Map Calculation for MRI Diffusion Image Processing
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional methods for processing magnetic resonance diffusion image data require acquiring multiple images with different b-values, leading to long measurement times and unnecessary data, as the optimal b-value for tissue differentiation is unknown, resulting in a high workload for experts who must sift through numerous images.
Innovation Solution
A method that calculates a b-value map based on diffusion image data and a predetermined signal threshold, allowing for the creation of a spatial distribution of b-values that highlights relevant tissue characteristics, reducing computing time and workload by generating a versatile map that includes virtual b-values, which can be displayed and assessed more efficiently.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple diffusion images with different b-values are acquired to improve tissue differentiation, then measurement precision is improved, but measurement time increases
Solution Approach 1:
The patent performs preliminary calculation of a b-value map from the acquired diffusion images before expert assessment. This preliminary processing identifies which b-values provide optimal tissue differentiation, eliminating the need for experts to manually evaluate multiple diffusion images and reducing assessment time while maintaining diagnostic accuracy.
Solution Approach 2:
The patent extracts only the essential information (optimal b-value ranges for tissue differentiation) from the complete set of diffusion images by generating a b-value map. This extraction process separates the relevant diagnostic information from unnecessary data, allowing experts to focus on only the most informative parameters.
2Measurement precision
If multiple diffusion images with different b-values are acquired to improve tissue differentiation, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent introduces a b-value map as an intermediary representation between the raw diffusion images and expert assessment. This intermediate data structure simplifies the complexity by transforming multiple complex diffusion images into a single intuitive map that highlights optimal b-values, making the data more manageable and easier to interpret.
Solution Approach 2:
The patent creates a simplified copy (b-value map) of the essential information from multiple diffusion images. This copy contains the critical diagnostic information in a condensed format, allowing experts to assess tissue differentiation without dealing with the full complexity of multiple high-resolution diffusion images.
3Measurement precision
If multiple diffusion images are calculated with virtual b-values to improve tissue differentiation, then measurement precision is improved, but computing time increases
Solution Approach 1:
The patent performs preliminary calculation of a b-value map from the acquired diffusion images before expert assessment. This preliminary processing identifies which b-values provide optimal tissue differentiation, eliminating the need for experts to manually evaluate multiple diffusion images and reducing assessment time while maintaining diagnostic accuracy.
Data Source
AI summary
In a method, a user interface, a magnetic resonance apparatus, and a storage medium encoded with programming instructions, in order to enable processing and/or display of magnetic resonance diffusion image data, diffusion image data are provided to a computer, a signal threshold are provided to a computer, and a b-value map is calculated by the computer on the basis of the diffusion image data and the predetermined signal threshold.