MRI Apparatus Pulse Sequence Selection for Image Quality
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Solution Overview
Problem
Magnetic resonance imaging (MRI) techniques face challenges in maintaining consistent image quality due to subject motion, particularly during breathing, leading to variable results that depend heavily on the technician's skill, necessitating reattempts and potentially differing imaging outcomes.
Innovation Solution
An MRI apparatus equipped with processing circuitry that collects and analyzes magnetic resonance data to determine image quality, selecting a re-collection pulse sequence with differing types or conditions if initial image quality does not meet criteria, utilizing machine learning to generate a trained model for optimizing pulse sequence selection and reducing technician dependence.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a technician manually judges and reattempts imaging when image quality is insufficient, then imaging can be corrected, but the results vary greatly depending on technician skill level
Solution Approach 1:
The imaging apparatus automatically determines image quality and selects re-collection pulse sequences without technician intervention. The processing circuitry evaluates image quality metrics and autonomously decides whether re-imaging is needed, eliminating technician skill dependence while maintaining reliable image quality standards
Solution Approach 2:
The system implements a feedback loop where image quality is continuously monitored and evaluated. When quality thresholds are not met, the system automatically triggers re-collection with adjusted parameters, creating a closed-loop control system that ensures consistent image quality regardless of technician expertise
2Productivity
If the same pulse sequence is used for re-attempt imaging, then the imaging process is simple, but failure is likely if the subject's body motion occurred during initial imaging
Solution Approach 1:
The system dynamically adjusts pulse sequence parameters based on the cause of imaging failure. When body motion is detected as the reason for poor image quality, the processing circuitry automatically selects different imaging conditions or sequences suited for motion compensation, rather than statically repeating the same sequence
Solution Approach 2:
The system changes imaging parameters such as pulse sequence type, timing, or acquisition conditions when re-attempting imaging. This parameter adaptation increases the likelihood of successful image acquisition by matching the re-collection settings to the specific conditions that caused the initial failure
3Reliability
If multiple re-attempts are performed with different pulse sequences, then image quality can be improved, but imaging time and complexity increase
Solution Approach 1:
The system performs preliminary evaluation of image quality immediately after acquisition. By quickly assessing whether the image meets quality thresholds, the system determines early whether re-collection is needed, avoiding unnecessary delays when images are acceptable and enabling targeted re-attempts only when necessary
Solution Approach 2:
The system applies re-collection only to specific imaging sequences or regions that failed quality checks, rather than re-attempting all imaging. This selective approach maintains high image quality standards while minimizing overall imaging time by focusing resources only where needed
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach enables consistent and high-quality MR imaging by automatically selecting appropriate pulse sequences, reducing variability and reliance on technician expertise, thereby improving imaging efficiency and consistency.
Implementation Method 1
Magnetic resonance imaging (MRI) techniques face challenges
Data Source
AI summary
According to one embodiment, a magnetic resonance imaging apparatus includes processing circuitry. The processing circuitry collects magnetic resonance data in accordance with a pulse sequence. The processing circuitry determines image quality based on the magnetic resonance data. The processing circuitry selects a re-collection pulse sequence when it is determined that the image quality does not satisfy criteria, the re-collection pulse sequence having at least one of a type of sequence or an imaging condition differing from that of the pulse sequence.