Monochromatic Image Energy Value Selection via Scout Noise Signal
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Solution Overview
Problem
Conventional medical imaging apparatuses, such as CT scanners, lack the ability to automatically select an optimal energy value for generating monochromatic images, often relying on user experience without considering the patient's specific body characteristics, which can affect image quality due to varying noise signal magnitudes.
Innovation Solution
A medical imaging apparatus and method that determine the magnitude of noise signals in scout images, calculate corresponding physical quantities, and adjust the energy value of monochromatic images based on these measurements, using a mapping table to optimize image generation according to the patient's body size and noise levels.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If monochromatic image is reconstructed based on arbitrarily selected energy value without considering optimal energy value, then device complexity is reduced, but image quality deteriorates due to varying noise signal magnitudes across different patient body sizes
Solution Approach 1:
The system automatically determines the optimal energy value by itself based on the scout image noise signal magnitude, eliminating the need for manual user selection. The image processor calculates the noise signal magnitude from the scout image, maps it to a physical quantity, and automatically selects the corresponding energy value, making the system self-adjusting to different patient body sizes.
Solution Approach 2:
The system changes the energy value parameter based on the determined noise signal magnitude and corresponding physical quantity. By establishing a mapping relationship between noise signal magnitude and optimal energy value, the system dynamically adjusts the energy value parameter to match the patient's body characteristics, thereby optimizing image quality.
2Manufacturing precision
If automatic energy value selection based on noise signal magnitude is implemented, then image quality is improved for different patient body sizes, but device complexity increases due to additional processing steps
Solution Approach 1:
The system performs preliminary determination of the noise signal magnitude from the scout image before the actual monochromatic image reconstruction. By calculating the noise signal magnitude and determining the corresponding energy value in advance, the system prepares the optimal parameters beforehand, ensuring image quality without adding complexity to the main reconstruction process.
Solution Approach 2:
The noise signal magnitude serves as an intermediary parameter that connects the patient's body characteristics (physical quantity) to the optimal energy value. The system uses this intermediary to translate anatomical information from the scout image into the appropriate imaging parameters, simplifying the overall control logic while maintaining image quality.
3Measurement precision
If energy value is adjusted according to patient body size, then measurement precision of physical quantity is improved, but ease of operation deteriorates due to automated processing
Solution Approach 1:
The system automatically determines the energy value without requiring manual input from the operator. The image processor independently calculates the noise signal magnitude, maps it to the corresponding physical quantity, and selects the appropriate energy value, making the system self-sufficient and eliminating the need for manual intervention.
Solution Approach 2:
The system uses feedback from the scout image noise signal magnitude to automatically adjust the energy value for monochromatic image reconstruction. By continuously monitoring the noise signal and adjusting the energy value accordingly, the system ensures optimal image quality while reducing operational complexity.
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 allows for the automatic selection of optimal energy values for generating high-quality monochromatic images tailored to the patient's body size, enhancing image accuracy and quality without manual intervention.
Implementation Method 1
the image processor determines a magnitude of a noise signal of a scout image of an object
Implementation Method 2
an X-ray detector configured to detect X-rays generated by the X-ray generator and received through the object
Implementation Method 3
an X-ray generator configured to emit X-rays
Data Source
AI summary
A medical imaging apparatus may include an image processor configured to generate an image based on data acquired by an X-ray detector, wherein the image processor determines a magnitude of a noise signal of a scout image of an object, determines a physical quantity of the object corresponding to the determined magnitude of the noise signal, determines an energy value of a monochromatic image by comparing the determined physical quantity of the object and a preset reference physical quantity, and generates the monochromatic image corresponding to the determined energy value.