Radiography Mode Selection Using Automatic Grid Detection
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Solution Overview
Problem
Existing radiography systems experience a decrease in efficiency when switching between fluoroscopy and general imaging modes due to the need for manual mode selection by the user.
Innovation Solution
A radiography system that automatically selects between fluoroscopy and general imaging modes based on information related to the grid used in capturing the radiation image, setting appropriate imaging and image processing conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If manual mode selection is implemented between fluoroscopy and general imaging, then the system can accurately adapt to different imaging requirements, but the imaging efficiency decreases due to frequent manual switching
Solution Approach 1:
The system automatically detects grid information from captured images and self-determines the appropriate imaging mode (fluoroscopy or general imaging) without requiring manual user input. The processor analyzes grid presence and type to automatically select imaging conditions, enabling the system to serve itself in mode selection tasks.
Solution Approach 2:
The system captures initial images, analyzes grid information from these images, and uses this feedback to automatically adjust and determine subsequent imaging modes and conditions. This closed-loop feedback mechanism allows the system to adapt imaging parameters based on real-time detection of grid presence and characteristics.
2Productivity
If automatic mode selection is implemented, then the imaging efficiency is improved by eliminating manual switching, but the system complexity increases due to automated detection and decision-making mechanisms
Solution Approach 1:
The existing image capture and processing functions are extended to perform multiple tasks: capturing images for diagnostic purposes while simultaneously analyzing grid information for automatic mode selection. The processor performs both diagnostic image processing and grid detection functions using the same hardware resources, avoiding the need for separate dedicated components.
Solution Approach 2:
The grid detection function is merged with the existing image processing workflow. The system combines grid information analysis with routine image capture and processing operations, integrating multiple functions into a unified process that operates within the existing system architecture without requiring separate independent subsystems.
3Measurement precision
If grid information analysis is performed for every image, then the accuracy of mode selection is improved, but the processing time and computational load increase
Solution Approach 1:
The system performs grid information analysis on initial capture images before final mode determination. By analyzing grid presence and type in advance from these preliminary images, the system prepares mode selection decisions ahead of time, reducing processing delays during actual imaging operations.
Solution Approach 2:
The system performs grid analysis selectively on key frames or initial images rather than every single image frame. This partial action approach provides sufficient accuracy for mode determination while significantly reducing the overall computational burden and processing time compared to analyzing every image.
Data Source
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AI summary
Provided are a radiography system, a radiography method, and a radiography program that can suppress a decrease in efficiency of radiographic imaging. A radiography system capable of executing fluoroscopy in which a plurality of radiation images are continuously captured at a predetermined frame rate and general imaging in which one radiation image is recorded in a switchable manner, the radiography system selects the fluoroscopy or the general imaging as an imaging mode of the radiation image based on information related to a grid used in capturing the radiation image.