Spectral CT Data Correction for Artifact Reduction
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Spectral computed tomography (CT) images suffer from artifacts due to errors in data prior to material decomposition, which are amplified during the decomposition process, leading to issues like streak artifacts and degraded contrast-to-noise ratio, and current methods to minimize these errors restrict data acquisition modes, increasing examination time and risk of motion artifacts.
Innovation Solution
A method that involves receiving CT measurement data, determining error estimates for each set of measurement values, defining replacement reference values, and applying a function to map measurement values to corrected values based on error estimates, ensuring the corrected values are between the original measurement and the replacement reference values, thereby reducing the impact of errors on image reconstruction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Object-affected harmful factors
If x-ray beam collimation is reduced to minimize scattered radiation, then scattered radiation is reduced, but examination time increases and motion artifact risk increases
Solution Approach 1:
The patent applies preliminary action by performing error estimation and data correction before material decomposition. The system identifies erroneous measurement values and corrects them using replacement reference values derived from non-erroneous data, thereby preventing artifact formation in advance rather than dealing with artifacts after acquisition
Solution Approach 2:
The patent changes the parameter state of measurement data by transforming erroneous values into corrected values based on error estimates. The correction process adjusts affected measurement values using a function that combines original measurements with replacement reference values, effectively changing the data quality parameter to enable artifact-free reconstruction
2Measurement precision
If calibration and computational correction steps are intensified to minimize data errors, then data accuracy is improved, but device complexity and processing effort increase
Solution Approach 1:
The patent applies local quality by treating different measurement data points differently based on their error characteristics. Instead of uniformly processing all data, the system identifies specifically erroneous measurement values and applies correction only to those locations, leaving unaffected data unchanged. This localized approach reduces computational complexity compared to global correction methods
3Loss of information
If material decomposition is performed on data with errors, then spectral information is extracted, but artifacts are amplified and image quality degrades
Solution Approach 1:
The patent applies preliminary anti-action by counteracting the harmful effect of errors before material decomposition occurs. The system estimates errors in measurement data and corrects erroneous values using replacement reference values derived from the same data set, thereby preventing the amplification of artifacts during subsequent decomposition processes
Data Source
AI summary
A method comprises: receiving computed tomography measurement data with sets of measurement values, wherein a set corresponds to a detector element readout of the measurement data including measurement values from at least two different x-ray spectra; determining an error estimate per set of measurement values; defining a replacement reference value per set of measurement values; applying a function that maps the measurement values to corrected values, the corrected values being between the mapped measurement value and the replacement reference value of the respective set, such that for larger errors the corrected value is closer to or at the replacement reference value and for smaller errors the corrected value is closer to or at the measurement value; and reconstructing computed tomography image data based on the corrected values.