X-ray C-arm Collision Prevention Using Video Camera Volume Scanning
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Solution Overview
Problem
Modern x-ray imaging systems, particularly x-ray C-arm systems, face challenges in predicting obstacles during the movement of their movable parts, leading to time-consuming slow test runs that may not guarantee accident prevention and delay interventional operations.
Innovation Solution
The method employs multiple video cameras to divide the space into volume elements, capturing and analyzing whether these elements are occupied, allowing for predictive collision detection and preventing target movements if obstacles are present, thereby eliminating the need for slow test runs and enabling immediate movement execution when safe.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a slow test run is carried out to prevent collisions, then safety is improved, but time consumption increases
Solution Approach 1:
The system performs preliminary scanning of the movement path using video cameras before the actual movement to detect obstacles in advance. This preliminary detection allows the system to plan safe movements without requiring slow test runs, thus maintaining safety while reducing time consumption.
Solution Approach 2:
The patent replaces the mechanical approach of slow test runs with an optical detection system using video cameras and image processing. Instead of physically moving the C-arm slowly to detect obstacles, the system uses cameras to capture images and algorithms to predict potential collisions, substituting mechanical verification with optical sensing and computational analysis.
2Reliability
If a slow test run is performed to ensure safety, then reliability is improved, but productivity deteriorates
Solution Approach 1:
The system replaces time-consuming mechanical test runs with rapid optical detection and computational prediction. Video cameras capture images of the environment, and image processing algorithms analyze these images to predict potential collisions before movement begins, enabling safe operations without sacrificing productivity.
Solution Approach 2:
The system performs preliminary environmental scanning and path analysis before actual movements. By detecting obstacles in advance through video imaging and performing collision prediction computations beforehand, the system ensures safety while allowing rapid execution of interventional operations without delays.
3Loss of time
If video cameras are used for real-time obstacle detection, then time efficiency is improved, but device complexity increases
Solution Approach 1:
The video cameras serve multiple functions: they capture images for collision prediction, provide real-time monitoring during operations, and can be reused for different movement scenarios. This multi-functionality justifies the added device complexity by providing comprehensive safety and efficiency benefits across various operational contexts.
Solution Approach 2:
The system introduces video cameras as intermediary sensing elements between the C-arm and the environment. Rather than requiring direct physical interaction or complex mechanical sensors, the cameras act as mediators that capture visual information, which is then processed by algorithms to detect obstacles and predict collisions, simplifying the overall sensing approach despite adding camera hardware.
Data Source
AI summary
With an x-ray imaging system with a moveable part, obstacles can stand in the way of the movement of the moveable part. In accordance with the invention, video cameras capture the occupation of the space by objects using volume elements. It is possible to determine at a target movement of the moveable part which volume elements are passed through during this. If one of these volume elements proves to be a volume element occupied by an object, the movement of the moveable part is prevented, otherwise it is enabled or actively implemented.