Radiation Therapy Controller Selective CT Image Update
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Solution Overview
Problem
The Iterative Reconstruction method for generating CT images improves image quality but increases calculation time due to repeated processes of error reflection and image reconstruction to minimize pixel errors, which is inefficient for radiation therapy device controllers.
Innovation Solution
A radiation therapy device controller that selects CT image data based on body motion phases, generates radiation projection images at various angles, calculates luminance update amounts for each pixel, and updates CT image data only for pixels with significant luminance changes, allowing for efficient high-quality image generation and accurate diseased portion tracking.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If the Iterative Reconstruction method is used to generate CT images, then image quality is improved, but calculation time increases due to repeated error reflection and image reconstruction processes
Solution Approach 1:
The patent pre-calculates and stores correction data (projection images and correction values) for multiple respiratory phases before actual treatment. This preliminary preparation allows the system to quickly retrieve and apply pre-computed corrections during real-time treatment without performing full iterative reconstruction, thus maintaining high image quality while reducing calculation time.
Solution Approach 2:
The patent divides the CT image into multiple regions of interest (ROIs) based on anatomical structures and motion characteristics. By applying iterative reconstruction only to specific ROIs where high precision is needed rather than the entire image, the system maintains diagnostic quality in critical areas while significantly reducing overall calculation time.
2Measurement precision
If CT image quality is improved to accurately identify diseased portion position, then radiation targeting accuracy is improved, but processing time increases
Solution Approach 1:
The patent applies different processing strategies to different regions of the CT image based on their importance and motion characteristics. High-resolution iterative reconstruction is applied only to regions containing the diseased portion or critical anatomical structures, while other regions use faster reconstruction methods, thus maintaining positioning accuracy for radiation targeting while reducing overall processing time.
Solution Approach 2:
The system pre-identifies and marks regions of interest containing the diseased portion before treatment. These pre-identified ROIs are then used to guide the selective application of high-quality reconstruction algorithms only where needed for accurate disease localization, avoiding unnecessary processing of entire images and reducing overall processing time.
Data Source
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AI summary
A radiation therapy device controller identifiesa pixel on a straight line connecting a ray source and a sensor array, and calculates a luminance update amount candidate value for each identified pixel based on a ratio of a change amount for the pixel on the straight line indicating the living body to a sum of change amounts from a luminance value of a pixel corresponding to a correlated computed tomography image correlated with a computed tomography image of an update target of a luminance value of the identified pixel. Also, the control device calculates a luminance update amount of each identified pixel using the luminance update amount candidate value of each identified pixel calculated for a plurality of rotation angles, and updates the luminance value of each corresponding pixel of the computed tomography image of the update target using the luminance update amount of each identified pixel.