Automatic Dose Rate Control for Dynamic X-ray Imaging
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Solution Overview
Problem
Automatic dose rate control (ADRC) systems in fluoroscopy struggle to maintain optimal contrast-to-noise ratio (CNR) in X-ray images, especially when patient thickness increases or higher density materials are introduced, leading to reduced visibility of objects of interest like guide wires or iodinated blood vessels.
Innovation Solution
An imaging apparatus and method that automatically identifies and localizes objects and background regions of interest using computer vision techniques, such as deep neural networks, to determine normalized X-ray attenuation factors, allowing for real-time adjustment of X-ray exposure settings to optimize CNR.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Illumination intensity
If automatic dose rate control maintains image brightness at target level, then detector pixel value is optimized, but contrast to noise ratio decreases significantly as patient thickness increases
Solution Approach 1:
The patent applies local quality by differentiating between background ROI and object ROI processing. The system calculates normalized X-ray attenuation factors specifically for background regions to determine exposure settings, while separately evaluating object visibility and CNR in object regions. This allows optimization of image brightness in background areas without compromising contrast-to-noise ratio in object areas, resolving the contradiction between maintaining target brightness and preserving measurement precision.
Solution Approach 2:
The system dynamically changes exposure parameters (mA, kV, pulse width) based on real-time calculation of normalized X-ray attenuation factors derived from background ROI analysis. By continuously adjusting these parameters to maintain target CNR rather than just target brightness, the system adapts to varying patient thickness and density, preventing CNR degradation while maintaining adequate image brightness.
2Loss of information
If higher density materials are introduced into the field of view, then diagnostic information is improved, but contrast to noise ratio of other objects decreases
Solution Approach 1:
The system responds to introduced high-density materials by recalculating normalized X-ray attenuation factors and adjusting exposure parameters (mA, kV, pulse width) in real-time. This dynamic parameter adjustment compensates for the increased attenuation caused by high-density materials, maintaining adequate CNR for other objects of interest while preserving the diagnostic information provided by the introduced materials.
Solution Approach 2:
The patent implements a closed-loop feedback system that continuously monitors image quality metrics including CNR and normalized attenuation factors. When high-density materials are detected or CNR degradation is identified, the system provides feedback to adjust exposure parameters, ensuring that diagnostic information from introduced materials is preserved while maintaining visibility of other objects.
3Measurement precision
If real-time adjustment of X-ray exposure parameters is implemented, then contrast to noise ratio is optimized, but system complexity increases
Solution Approach 1:
The system employs automated algorithms that perform real-time CNR optimization without requiring manual intervention. The processing circuitry automatically identifies background ROI, calculates normalized X-ray attenuation factors, determines optimal exposure parameters, and adjusts settings autonomously. This self-service capability achieves real-time CNR optimization while minimizing the operational complexity burden on users.
Solution Approach 2:
The patent pre-calculates and stores lookup tables for normalized X-ray attenuation factors based on known material densities and thicknesses. This preliminary preparation allows the real-time system to quickly reference and apply appropriate exposure adjustments without performing complex calculations during image acquisition, reducing computational complexity while maintaining optimization effectiveness.
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
This approach enables real-time optimization of X-ray exposure parameters, improving the visibility of objects of interest by maintaining a target CNR, even in varying patient thicknesses and densities, thereby enhancing image quality without unnecessary dose penalties.
Implementation Method 1
The attenuation of the radiation that has passed through the body is measured by processing electrical signals received from the detector
Data Source
AI summary
A method of imaging includes obtaining a first image including projection data representing an intensity of X-rays detected by a plurality of detectors at a first X-ray exposure setting, the X-rays being emitted from an X-ray source; based on a detection result of a first object in the first image: determining a background region of interest (ROI) around the first object, the background ROI including background ROI pixels having a first intensity value corresponding to the intensity of the X-rays; and converting, for each pixel of the background ROI pixels, the first intensity values of the background ROI pixels to a normalized X-ray attenuation factor; and determining a second X-ray exposure setting for use in obtaining a second image based on the background ROI pixels converted to the normalized X-ray attenuation factor.