Personalized X-ray Parameter Optimization for Radiation Safety
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Solution Overview
Problem
Current medical imaging technologies, such as X-ray and CT scanners, expose patients to excessive radiation due to arbitrary parameter settings, which can be harmful, especially for pregnant women, and result in suboptimal image quality.
Innovation Solution
A method and apparatus that generate personalized parameter values for X-ray imaging by analyzing first and second medical images, determining standard parameter values from a lookup table based on body information and image characteristics, and adjusting radiation settings to optimize image quality while minimizing exposure.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If arbitrary parameter values are used for X-ray imaging, then the imaging process is simple and fast, but the radiation exposure to patients becomes excessive and harmful
Solution Approach 1:
The system dynamically adjusts X-ray imaging parameters (such as tube current, tube voltage, and exposure time) based on patient-specific information including body mass index, body part, and clinical indication. This parameter optimization ensures adequate image quality while minimizing radiation dose, resolving the contradiction between imaging efficiency and radiation safety.
Solution Approach 2:
The system incorporates feedback mechanisms where imaging parameters are continuously adjusted based on real-time information about patient characteristics and image quality requirements. The system uses lookup tables and algorithms that provide feedback on optimal parameter settings, enabling the balance between maintaining imaging productivity and reducing harmful radiation exposure.
2Ease of operation
If standardized parameter values are used for all patients, then the operation is simple, but the image quality becomes suboptimal for individual patients
Solution Approach 1:
The system applies local quality by customizing imaging parameters according to specific patient characteristics (body mass index, body part, age, sex) rather than using uniform settings for all patients. This allows optimal image quality for each individual while maintaining automated operation through lookup tables and algorithms that handle the complexity.
Solution Approach 2:
The system performs self-service by automatically selecting and adjusting optimal parameter values based on patient information entered into the system. The automated parameter selection through lookup tables and algorithms eliminates the need for manual optimization by operators, maintaining ease of operation while achieving personalized image quality.
3Manufacturing precision
If high radiation exposure is used, then the image quality is improved, but the harmful effects on patients especially pregnant women increase
Solution Approach 1:
The system optimizes radiation parameters (tube current, voltage, exposure time) to use the minimum necessary dose to achieve diagnostic image quality. By adjusting these parameters based on patient-specific factors, the system maintains adequate image quality while minimizing harmful radiation effects, particularly for vulnerable populations such as pregnant women.
Solution Approach 2:
The system converts the potentially harmful high radiation exposure into a beneficial controlled low-dose imaging process. By using optimized parameter settings and advanced image processing techniques, the system achieves diagnostic quality images at lower radiation levels, turning what would be a harmful exposure into a safe and effective diagnostic procedure.
4Object-affected harmful factors
If personalized parameter values are generated for each patient, then the radiation exposure is minimized, but the system complexity increases
Solution Approach 1:
The system uses lookup tables and algorithms as intermediaries between patient information and optimal parameter settings. These intermediaries pre-process and organize the complex relationships between patient characteristics and imaging parameters, simplifying the overall system architecture while enabling personalized parameter optimization that minimizes radiation exposure.
Solution Approach 2:
The system performs preliminary action by pre-calculating and storing optimal parameter combinations in lookup tables based on various patient characteristics and imaging conditions. This pre-processing eliminates the need for complex real-time calculations during patient imaging, reducing system complexity while maintaining personalized radiation dose optimization.
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 reduces unnecessary radiation exposure and ensures optimal image quality by tailoring radiation settings to individual patient characteristics, thereby minimizing re-imaging and enhancing image readability.
Implementation Method 1
X-ray image imaging apparatuses are equipment that observe an internal structure of an organic body by using X-rays
Data Source
AI summary
A method of generating a personalized parameter value for generating a medical image includes acquiring a first medical image of an object, which is imaged according to a predetermined parameter value set in a medical imaging apparatus, and a second medical image changed from the first medical image, determining a first standard parameter value corresponding to the first medical image and a second standard parameter value corresponding to the second medical image, and generating a personalized parameter value corresponding to the object on the basis of the first standard parameter value and the second standard parameter value.