Automated Critical Station Detection in MRI Scans
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Solution Overview
Problem
The manual selection of stations potentially affected by respiratory motion in multi-station scans is a tedious and time-consuming process, limiting patient throughput in hospitals.
Innovation Solution
A device comprising an input unit, processing unit, and output unit that analyzes optical image data to identify the spatial location of a patient's lung and align it with a planned multi-station scan, automatically assigning breath-hold instructions to critical stations affected by respiratory motion, using techniques like landmark detection and safety margins.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual selection of stations is used, then operator control and accuracy are maintained, but patient throughput is limited due to time-consuming procedures
Solution Approach 1:
The system performs automatic station selection by analyzing optical images to identify lung regions and automatically assigning breath-hold instructions, eliminating the need for manual operator intervention and significantly reducing the time required for station selection while maintaining accuracy
Solution Approach 2:
The patent replaces the manual mechanical process of visual inspection and station marking with an automated image processing system that uses optical cameras and computational algorithms to identify critical stations and assign breath-hold instructions automatically
2Productivity
If automated detection is implemented, then patient throughput is improved and time is reduced, but system complexity increases
Solution Approach 1:
The system introduces an intermediary optical imaging system and processing unit that acts as a mediator between the patient and the scan planning system, automatically extracting anatomical information and generating station assignments without requiring direct operator intervention in the complex analysis process
Solution Approach 2:
The patent uses optical images as a copy or representation of the patient's anatomy to automatically identify lung regions and determine critical stations, replacing the need for direct manual measurement and inspection with image-based automated detection
Data Source
AI summary
A device is provided for detecting critical stations in a multi-station scan. The device includes an input unit, a processing unit, and an output unit. The input unit is configured to receive image data taken from a patient lying on a table before start of a diagnostic scan with a magnetic resonance imaging system. The processing unit is configured to analyze the image data of the patient to identify a spatial location of the lungs of the patient to align the spatial location of the lungs of the patient with a planned multi-station scan to identify the critical stations that are potentially affected by a respiratory motion of the patient, and to assign breath-hold to the identified critical stations. The output unit is configured to provide the identified critical stations. Thus, the selection of critical stations can be automatically and consistently satisfied without operator intervention.