MRI Field of View Adjustment Using Distortion Maps
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Magnetic resonance imaging (MRI) scans face distortions due to imperfections in gradient fields, leading to unmapped regions at the edges of the field of view, which can result in missing information, especially in modern, openly configured MRI facilities, making it difficult for users to accurately set and plan the field of view.
Innovation Solution
The method involves using a distortion map to ascertain exclusion information about unmapped regions within the original field of view, applying inverse distortion correction to determine a second set of field of view parameters, and adjusting the scan parameters to ensure all desired regions are mapped, with optional user input and visualization tools to support field of view adjustments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If distortion correction is applied to eliminate gradient field imperfections, then image accuracy is improved, but the field of view is reduced due to unmapped regions at the edges
Solution Approach 1:
The system performs preliminary calculation of exclusion information based on the distortion map before the actual MRI scan. This allows the field of view to be pre-adjusted to compensate for upcoming distortion effects, ensuring that all regions including edge areas are properly mapped without losing information after distortion correction is applied.
Solution Approach 2:
The patent introduces a new dimension of planning by visualizing exclusion information and unmapped regions overlaid on the field of view. This additional visual layer allows users to understand and compensate for distortion effects in the spatial domain, transforming the abstract distortion problem into a visible planning tool that guides field of view selection.
2Reliability
If the field of view is set larger to cover edge regions, then completeness of coverage is improved, but the distortion effects become more pronounced and harder to estimate
Solution Approach 1:
The system provides visual feedback by displaying exclusion information and unmapped regions overlaid on the field of view. This feedback mechanism allows users to see exactly which areas will be affected by distortion and adjust the field of view accordingly, transforming the complex estimation problem into a straightforward visual adjustment process.
Solution Approach 2:
The distortion map serves as an intermediary between the gradient field imperfections and the field of view planning. By using this intermediate representation, the system translates complex distortion effects into actionable exclusion information that guides field of view selection, making the planning process more manageable and accurate.
3Adaptability or versatility
If users manually estimate and plan the field of view based on experience, then adaptability is improved, but the accuracy and consistency vary among different users
Solution Approach 1:
The system enables self-service by automatically calculating exclusion information and visualizing unmapped regions based on the stored distortion map. Users no longer need to rely on personal experience or manual estimation; instead, the system provides objective, consistent guidance that ensures accurate field of view planning while maintaining user control and flexibility in the final selection.
Data Source
AI summary
In a computer-implemented method for setting a field of view for a magnetic resonance scan, exclusion information describing a region of the original field of view that is unmapped owing to the distortion is ascertained on the basis of the distortion map for at least one first set of field-of-view parameters describing a rectangular or cuboidal original field of view, the exclusion information is used to determine a second set of field-of-view parameters to be used for the magnetic resonance scan, and the magnetic resonance scan is performed using the second set of field-of-view parameters.