X-Ray Imaging System Preshot ROI Detection and Exposure Control
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Solution Overview
Problem
Current X-ray imaging systems face challenges in accurately determining exposure parameters, particularly in pediatric and extremity imaging, where anatomical alignment issues lead to inconsistent radiation doses and low-quality images due to the reliance on fixed sensor locations, which are not adaptable to varying patient sizes and shapes, and are further complicated by the limitations of automatic exposure control systems in mobile radiography systems.
Innovation Solution
An X-ray imaging system that includes a radiation source, detector, camera, and control processing unit capable of generating preshot images to automatically identify regions of interest (ROIs) and adjust exposure parameters for optimized main shot imaging, using image processing circuitry and a user interface to determine ROI locations and adjust settings such as kVp, mA, and ms for improved image quality and reduced radiation dose.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual determination of exposure parameters is used, then operator flexibility is maintained, but image quality deteriorates and radiation dose increases due to subjective estimation errors
Solution Approach 1:
The system performs self-measurement of radiation exposure using integrated ionization chambers that automatically detect and quantify the radiation dose received by the patient during imaging, eliminating the need for manual estimation and enabling automatic adjustment of exposure parameters
Solution Approach 2:
The system implements feedback control by measuring actual radiation exposure in real-time through ionization chambers and using this information to automatically adjust exposure parameters for subsequent images, creating a closed-loop control system that optimizes both image quality and radiation dose
2Device complexity
If fixed sensor locations are used for AEC, then system simplicity is maintained, but measurement precision deteriorates in pediatric and extremity imaging due to misalignment with anatomy
Solution Approach 1:
The system transitions from fixed, static sensor locations to dynamic positioning capabilities where the imaging system can be moved and repositioned to align sensors with the specific anatomy being imaged, allowing adaptation to pediatric and extremity cases while maintaining measurement accuracy
Solution Approach 2:
The system divides the imaging area into multiple selectable regions of interest (ROIs) with dedicated sensor alignment for each region, allowing independent optimization of measurement precision for different anatomical areas such as pediatric bodies or extremities
3Area of stationary object
If multiple images are stitched together to form larger images, then imaging coverage is improved, but alignment difficulty increases making AEC measurement inaccurate
Solution Approach 1:
The system segments the large imaging area into multiple smaller regions, each with its own dedicated sensor alignment and AEC measurement capability, allowing accurate local measurements even when images are subsequently stitched together for comprehensive coverage
Solution Approach 2:
The system applies local optimization by aligning sensors specifically with the anatomy in each region being imaged, rather than relying on global alignment, ensuring measurement accuracy varies locally according to the specific anatomical features present in each field of view
4Productivity
If thickness variation across anatomy is not accounted for, then imaging speed is maintained, but radiation dose uniformity deteriorates across different ROIs
Solution Approach 1:
The system applies different exposure parameters and sensor alignment strategies to different regions based on local anatomical thickness variations, allowing each ROI to receive optimized radiation dosing while maintaining overall imaging efficiency through automated control
Solution Approach 2:
The system dynamically adjusts exposure parameters and sensor positioning based on real-time detection of anatomical thickness variations across different regions, enabling adaptive dose optimization without significantly impacting imaging speed through automated real-time control
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 system enables precise determination of ROI locations and optimized exposure parameters, reducing radiation dose variability and improving image quality by automatically adjusting settings based on preshot image data, even in challenging anatomical alignments and image pasting processes.
Implementation Method 1
X-rays are generated by an X-ray source and are directed towards a patient or other subject. The X-rays transfer through the subject, and are absorbed or attenuated by internal features.
Implementation Method 2
sensors in the form of one or more dose sensors, such as ion or ionization chambers or solid-state sensors, coupled with the X-ray detector which measure radiation exposure
Data Source
AI summary
According to one aspect of an exemplary embodiment of the disclosure, a system and method for determining the location of one or more regions of interest (ROIs) within one or more preshot images taken of an anatomy includes the steps of providing an imaging system having a radiation source, a detector, and a camera aligned with the detector. A control processing unit is operably connected to the radiation source, the detector and the camera to generate preshot images and a camera image(s) of the subject. The camera image and preshot images are employed to determine the location of one or more regions of interest (ROIs) within the preshot images, such that exposure parameters for the operation of the radiation source to obtain one or more main shots of the subject can be adjusted corresponding to the image data for the ROI from the one or more preshot images.