Adaptive CBCT Sampling Reduces Radiation Dose
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Solution Overview
Problem
Conventional CBCT imaging systems acquire images using uniform sampling, which can result in increased radiation doses to patients and may not provide optimal image quality.
Innovation Solution
The method and apparatus for acquiring a CBCT image based on adaptive sampling, which involves acquiring a plurality of image scanning points from a previous medical image, sorting and selecting these points based on quantitative values or entropy, and then reconstructing CBCT images using these adaptive sampling points to reduce radiation dose and improve image quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If uniform sampling is used to acquire CBCT images, then the sampling process is simple and consistent, but the radiation dose to the patient increases and image quality may not be optimal
Solution Approach 1:
The patent applies local quality by differentiating sampling strategies across different anatomical regions. Regions of interest (such as tumor areas or clinically significant structures) are identified from the planning CT image, and sampling density is increased in these regions while reducing sampling in less critical areas. This allows optimal image quality in clinically important regions while minimizing overall radiation exposure.
Solution Approach 2:
The patent changes the sampling parameter from uniform to adaptive based on quantitative analysis of the planning CT image. By calculating entropy or other quantitative metrics for different regions, the system dynamically adjusts sampling intervals and densities, transforming the sampling strategy from a fixed parameter to a variable one that adapts to local image characteristics and clinical requirements.
2Ease of operation
If uniform sampling is used to acquire CBCT images, then the acquisition process is straightforward, but image quality in regions of interest may not be optimal
Solution Approach 1:
The patent enhances image quality in regions of interest by applying local quality principles. Regions are segmented based on quantitative metrics (entropy, gray level distribution) from the planning CT, and sampling density is locally optimized for each region. This ensures high-resolution data acquisition in clinically critical areas while maintaining a relatively simple overall acquisition workflow.
Solution Approach 2:
The patent performs preliminary analysis of the planning CT image before the actual CBCT acquisition. By pre-identifying regions of interest and pre-calculating optimal sampling parameters based on the planning image characteristics, the system prepares a customized sampling scheme in advance, which then guides the acquisition process to ensure optimal image quality in critical regions.
3Manufacturing precision
If adaptive sampling based on quantitative values is used, then image quality in regions of interest is improved, but the complexity of the sampling process increases
Solution Approach 1:
The patent reduces process complexity by performing all quantitative analysis and sampling parameter optimization in advance, during the planning stage. The planning CT image is analyzed to identify regions of interest and calculate optimal sampling parameters before acquisition begins. This preliminary action creates a ready-to-use sampling scheme that simplifies the actual acquisition process while maintaining high image quality in critical regions.
Solution Approach 2:
The system performs self-service by automatically analyzing the planning CT image, identifying regions of interest, and generating the adaptive sampling scheme without requiring manual intervention. The quantitative metrics (entropy, gray level distribution) are automatically calculated, and the sampling parameters are self-optimized based on the image characteristics, reducing the burden on operators while achieving superior image quality.
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 reduction of radiation dose applied to the patient while maintaining or improving the quality of the CBCT images by selectively sampling regions of interest based on adaptive criteria.
Implementation Method 1
a radiation irradiator which is installed on the gantry to irradiate a radiation beam
Implementation Method 2
an image acquiring unit which is installed on the gantry to acquire an image by detecting a radiation beam which penetrates the target patient
Data Source
AI summary
According to the method and the apparatus for acquiring a CBCT image based on adaptive sampling according to the exemplary embodiment of the present disclosure, a final CBCT image is acquired by reconstructing a plurality of cone beam computed tomography (CBCT) images acquired based on adaptive sampling so that a dose applied to the target patient may be reduced.