Mobile X-Ray Acquisition With Marker-Based Distortion Correction
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Solution Overview
Problem
Mobile X-ray systems used in emergency departments and intensive care units suffer from projection distortions due to flexible positioning of the X-ray source and detector, complicating physical measurements on X-ray images.
Innovation Solution
A method using a marker with known geometry, detected via deep learning, to determine the position of the X-ray source relative to the patient, allowing for correction of projection distortions and precise physical measurements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If the X-ray source position is made flexible to accommodate life support devices, then the adaptability of the mobile X-ray system is improved, but projection distortion increases and measurement precision deteriorates
Solution Approach 1:
A marker with known geometry is introduced as an intermediary object between the X-ray source and the patient. The marker contains a rod with known dimensions that can be detected in the X-ray image to calculate the actual geometry of the imaging setup, enabling correction of projection distortions while maintaining flexible positioning
Solution Approach 2:
The system changes the parameter of geometric information by introducing a marker with known dimensions and geometry. This allows the system to determine the actual source-to-detector geometry and adjust measurements accordingly, transforming the distorted projection into measurable data
2Adaptability or versatility
If the X-ray source position is varied to accommodate different patient positions, then the versatility of the mobile X-ray system is improved, but projection distortion increases and manufacturing precision deteriorates
Solution Approach 1:
The marker serves as a mediator that bridges the gap between flexible positioning requirements and measurement precision needs. By detecting the marker's known geometry in the X-ray image, the system can calculate distortion parameters and correct them, allowing versatile positioning without sacrificing measurement accuracy
Solution Approach 2:
The patent replaces mechanical adjustment methods with a computational approach. Instead of mechanically constraining the X-ray source position to maintain constant geometry, the system uses image processing and mathematical calculations based on the marker to achieve precise measurements regardless of source position
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
Enables accurate physical measurements on mobile X-ray images by reducing projection distortions, facilitating tasks such as measuring endotracheal tube placement and lung nodule size.
Implementation Method 1
receiving an X-ray image and detecting a marker in the X-ray image
Data Source
AI summary
The invention concerns a method, a system, as software module and a use of a marker for mobile X-ray acquisition of a patient. Comprising the steps of detecting a marker in an X-ray image using a deep learning method, wherein the marker comprises a plate of known geometry and a rod, determining a position of the rod of the marker, analyzing a projection of the rod in the X-ray image, determining an position of the X-ray source above the patients bed based on the analyzed projection of the rod.