MRI Pre-Scan Determination Using Automatic MR Dataset Comparison
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Solution Overview
Problem
Current MRI systems require manual determination of pre-scanning needs, leading to increased operator workload and scan duration due to unexpected changes in adjustment data during or between scans, affecting image quality and patient experience.
Innovation Solution
A pre-scanning determining method and apparatus that automatically assesses consistency between MR datasets using a pre-scanning determining sequence, calculating metrics such as magnitude, cosine similarity, Minkowski distance, or Pearson correlation coefficient to decide if pre-scanning is necessary before the next scan.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If pre-scan is repeated after every imaging scan to ensure data consistency, then image quality and reliability are improved, but scan duration and patient time are increased
Solution Approach 1:
The system performs self-diagnosis by automatically comparing adjustment data between scans to determine whether pre-scan repetition is necessary, eliminating the need for manual operator assessment and enabling autonomous decision-making about data validity
Solution Approach 2:
The system implements a feedback mechanism where adjustment data from previous scans is compared with current scan parameters, and based on this comparison, the system automatically determines whether to repeat pre-scan, creating a closed-loop quality control system
2Reliability
If manual determination of pre-scan need is performed by operator, then scan parameters can be adjusted based on experience, but operator workload and scan preparation time are increased
Solution Approach 1:
The system performs self-diagnosis by automatically comparing adjustment data between scans to determine whether pre-scan repetition is necessary, eliminating the need for manual operator assessment and enabling autonomous decision-making about data validity
Solution Approach 2:
The manual assessment process is replaced with an automated computational system that uses algorithms to compare adjustment data, substituting human operator judgment with machine-based automated determination
3Measurement precision
If full pre-scan is performed before every imaging scan to ensure complete data acquisition, then measurement precision is improved, but productivity and scan efficiency are reduced
Solution Approach 1:
Instead of performing a complete pre-scan before every imaging scan, the system performs a partial assessment by comparing key adjustment data parameters, executing the full pre-scan only when necessary based on the comparison results
Solution Approach 2:
The system performs a preliminary comparison of adjustment data before deciding whether to proceed with full pre-scan, allowing early identification of cases where complete pre-scan can be skipped
Data Source
AI summary
A pre-scanning determining method and apparatus, and a magnetic resonance imaging system. The method includes: scanning, after each magnetic resonance (MR) imaging scan ends and before a next MR imaging scan begins, an imaging target by using a pre-scanning determining sequence, and collecting a corresponding MR dataset according to a preset position and a preset quantity of a K-space line that needs to be collected; calculating, according to an MR dataset collected this time and an MR dataset collected last time by using the pre-scanning determining sequence, consistency between the two MR datasets; and determining, according to the consistency between the two MR datasets, whether pre-scanning needs to be performed before a next MR imaging scan begins.