Ghost Artifact Reduction in MRI EPI via Higher-Order Phase Corrections
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Solution Overview
Problem
Echo planar imaging (EPI) in magnetic resonance imaging (MRI) suffers from ghost artifacts due to phase errors, especially when imaging with a large field of view, which can lead to inaccurate diagnoses as ghost artifacts may be mistaken for anatomical structures.
Innovation Solution
A method is introduced that involves acquiring a non-phase-encoded reference dataset, calculating phase corrections for spatial orders higher than first order, and applying these corrections to a phase-encoded k-space dataset to reconstruct images, effectively reducing ghost artifacts by correcting higher-order phase errors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If echo planar imaging is used to achieve ultrafast imaging, then imaging speed is improved, but ghost artifacts are generated due to phase errors
Solution Approach 1:
The patent applies preliminary action by acquiring a reference dataset before the actual imaging data and calculating phase correction values in advance. These correction values are then applied during image reconstruction to eliminate ghost artifacts, thus resolving the contradiction between fast imaging speed and artifact generation.
2Measurement precision
If phase corrections are applied to reduce ghost artifacts, then image quality is improved, but computational complexity increases
Solution Approach 1:
The patent applies local quality by calculating phase correction values specifically for regions where ghost artifacts occur, rather than uniformly processing the entire dataset. This targeted approach reduces computational complexity while maintaining image quality improvement.
3Object-generated harmful factors
If higher-order phase corrections are calculated, then ghost artifact reduction is improved, but processing time increases
Solution Approach 1:
The patent applies partial action by implementing phase corrections up to a practical order (second or third order) rather than calculating all possible higher-order corrections. This provides sufficient ghost artifact reduction while avoiding excessive processing time, thus resolving the contradiction between artifact reduction and processing time.
Data Source
AI summary
Various methods and systems are provided for ghost artifact reduction in magnetic resonance imaging (MRI). In one embodiment, a method for an MRI system comprises acquiring a non-phase-encoded reference dataset, calculating phase corrections for spatial orders higher than first order from the non-phase-encoded reference dataset, acquiring a phase-encoded k-space dataset, correcting the phase-encoded k-space dataset with the phase corrections, and reconstructing an image from the corrected phase-encoded k-space dataset. In this way, ghost artifacts caused by phase errors during EPI may be substantially reduced, thereby improving image quality especially when imaging with a large field of view.