Iterative Reconstruction Parameter Table for X-ray CT Noise Reduction
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing X-ray CT devices face challenges in accurately determining iterative reconstruction parameters for reducing noise and radiation exposure, particularly in tissues with varying CT values, which affects image quality and diagnostic accuracy.
Innovation Solution
An X-ray CT device with an iterative approximation reconstruction unit that uses a table to determine parameters based on noise or X-ray reduction ratios, allowing for iterative correction of CT images to achieve desired noise reduction ratios without relying on specific CT image conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If iterative reconstruction is used to reduce noise and radiation exposure, then image quality and diagnostic accuracy improve, but the calculation amount increases and parameter optimization becomes more complex
Solution Approach 1:
The patent pre-calculates and stores the relationship between iterative reconstruction parameters and noise reduction ratios in a table before actual image reconstruction. This preliminary action allows the system to quickly retrieve appropriate parameters without performing complex real-time calculations, thereby reducing computational complexity while maintaining image quality.
Solution Approach 2:
The patent introduces a table as an intermediary between the iterative reconstruction algorithm and the final CT image. The table stores pre-computed relationships between parameters and noise reduction ratios, serving as a lookup mechanism that simplifies the complex parameter optimization process while preserving the noise reduction benefits of iterative reconstruction.
2Measurement precision
If iterative reconstruction with multiple parameters is used to achieve desired noise reduction, then noise reduction ratio improves, but the calculation time and computational load increase
Solution Approach 1:
The system performs noise reduction ratio calculations and parameter optimizations in advance, storing the results in a table. During actual clinical use, the system simply retrieves pre-determined parameters from the table based on the desired noise reduction ratio, avoiding time-consuming iterative calculations while maintaining the desired noise reduction效果.
Solution Approach 2:
The patent creates a simplified copy of the complex iterative reconstruction process in the form of a pre-computed table. Instead of performing the full iterative reconstruction with multiple parameters each time, the system uses the table as a reference, significantly reducing calculation time while preserving the essential noise reduction functionality.
3Ease of operation
If ROI is set in uniform tissue for SD measurement, then noise measurement becomes simpler, but accurate SD measurement in tissues with varying CT values becomes difficult
Solution Approach 1:
The patent pre-calculates the relationship between iterative reconstruction parameters and noise reduction ratios and stores it in a table. This allows the system to determine appropriate parameters without needing to perform complex real-time SD measurements in heterogeneous tissues, as the parameters are already optimized based on pre-computed data.
Solution Approach 2:
The patent uses a pre-computed table as an intermediary to bridge the gap between simple ROI-based SD measurement and accurate noise characterization in heterogeneous tissues. The table contains pre-determined parameters that account for tissue heterogeneity, allowing the system to achieve accurate noise reduction without complex real-time measurements.
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
Enables the determination of iterative reconstruction parameters to achieve desired noise reduction ratios, improving image quality and reducing radiation exposure across varying tissue conditions, thereby enhancing diagnostic accuracy.
Implementation Method 1
an X-ray generation unit for generating X-ray
Implementation Method 2
a forward projection calculation from the CT image
Data Source
AI summary
This X-ray CT device uses iterative reconstruction to obtain a CT image with the desired noise reduction or X-ray reduction ratio. An iterative approximation reconstruction unit (136) is provided which, from measured projection data obtained by an X-ray detection unit of the X-ray CT device, iteratively reconstructs a CT image in a reconstruction range of a subject, and iteratively corrects the CT image such that calculated projection data, calculated through forward projection of a CT image, is the same as the difference between measured projection data detected by the X-raw detection unit and calculated projection data. The iterative approximation reconstruction unit is provided with a parameter determination unit (151), an iterative correction unit (152), and a table unit (153) which calculates in advance the relation between each parameter used in the iterative reconstruction, and noise reduction or X-ray reduction ratio in the CT image. The parameter determination unit (151) determines the parameters from a calculation table in the table unit (153) depending on the desired reduction ratio.