Collimation Edge Detection in Digital Radiography
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional X-ray systems face challenges in precisely locating collimation edges in X-ray images, especially when feedback from mechanical positioners is incomplete or non-existent, leading to less than precise data and inconvenient manual input for image processing.
Innovation Solution
A computer-based system that detects collimation edges directly from the X-ray image data, using image processing techniques such as edge detection, Radon transform, and statistical analysis to generate collimation edge data for precise localization and image cropping.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If positioner feedback is used for collimation edge localization, then the process is automated, but the measurement precision deteriorates due to incomplete or non-existent feedback data
Solution Approach 1:
The patent introduces an intermediary computational model that maps positioner data to collimation edge locations. This mediator layer processes and interprets the positioner feedback data, allowing the system to use available automated data while compensating for its imperfections through algorithmic correction and validation against image-based features.
Solution Approach 2:
The system implements a feedback mechanism where the detected collimation edges from the image are compared with expected positions from positioner data. This closed-loop feedback allows the system to validate and refine edge localization, improving precision by cross-referencing multiple data sources and correcting discrepancies.
2Measurement precision
If manual input is used for collimation edge data, then measurement precision can be maintained, but ease of operation deteriorates due to operator burden
Solution Approach 1:
The system performs self-service by automatically detecting collimation edges directly from the X-ray image data without requiring manual operator input. The algorithm autonomously identifies edge features, determines their locations, and integrates this information into the imaging workflow, eliminating the need for operators to manually enter or adjust collimation edge data.
Solution Approach 2:
The patent replaces the manual mechanical input process with an automated image processing system. Instead of operators using keyboards or mice to input data, the system uses computational algorithms to automatically extract and process collimation edge information from the digital image, substituting human interaction with automated computational methods.
3Device complexity
If positioner feedback is integrated into fixed X-ray systems, then device complexity is reduced, but measurement precision worsens due to lack of rotation-angle feedback
Solution Approach 1:
The system compensates for the lack of rotation-angle feedback by changing the parameters used for edge detection. Instead of relying on precise angular position data, the algorithm uses image intensity gradients, edge detection filters, and spatial relationship analysis to determine collimation edge locations, adapting to the available data parameters.
Solution Approach 2:
The patent transitions from relying solely on one-dimensional positioner feedback data to utilizing two-dimensional image space information. By analyzing the spatial distribution of X-ray intensities and edge features across the image plane, the system extracts collimation edge location information from a different dimensional domain, compensating for the limitations of positioner feedback.
Data Source
AI summary
Systems, methods and apparatus are provided through which collimation edges in an X-ray image are located from information in the X-ray image.