CT Material Decomposition Using Pixel-Calibrated Projection Correction
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Solution Overview
Problem
Existing material decomposition methods in CT imaging face inaccuracies due to the difficulty in obtaining accurate emission spectrum curves of the radiation tube and energy response curves of the detector, leading to inaccurate images of decomposed materials.
Innovation Solution
A system that determines pixel parameters based on reference materials with consistent attenuation characteristics, correcting scan projection data to improve image accuracy by decomposing reconstructed images without needing to obtain these curves, using a model calibration process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional material decomposition methods are used relying on emission spectrum curves and energy response curves, then the decomposition process can be performed, but the accuracy of the decomposed material images deteriorates due to difficulty in obtaining accurate spectral data
Solution Approach 1:
The patent introduces pixel parameters as an intermediary element that mediates between the detector and the material decomposition process. Instead of directly using difficult-to-obtain emission spectrum curves and energy response curves, the system uses pixel parameters (which are easier to determine through calibration with reference materials) to correct projection data and achieve accurate material decomposition. This intermediary approach resolves the contradiction by replacing intractable measurements with more manageable calibration parameters.
Solution Approach 2:
The patent transforms the problem from using spectral curves (emission spectrum and energy response) to using pixel parameters. By changing the parameter representation from complex spectral functions to simpler pixel-level parameters that can be determined through calibration, the system maintains decomposition accuracy while avoiding the difficulty of obtaining precise spectral data. This parameter transformation is the core mechanism that resolves the technical contradiction.
2Measurement precision
If pixel parameters are determined through model calibration with reference materials, then the accuracy of projection data correction improves, but the complexity of the measurement process increases
Solution Approach 1:
The patent applies preliminary calibration action by determining pixel parameters using reference materials before performing the actual material decomposition on target objects. This preliminary calibration establishes the pixel parameters that will be used for correcting projection data throughout the measurement process. By performing this calibration step in advance, the system simplifies the main measurement process while ensuring high accuracy through pre-determined correction parameters.
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
The system achieves more accurate density distribution images of target materials by correcting projection data with pixel parameters, enhancing the accuracy of material decomposition results.
Implementation Method 1
a radiation source to obtain a plurality of sets of combined projection data of the at least two reference materials
Implementation Method 2
each of the at least two reference materials and a corresponding one of the at least two target materials may have substantially consistent attenuation characteristics
Data Source
AI summary
The present disclosure provides systems and methods for material decomposition. The systems may obtain scan projection data of a target object. The systems may determine corrected projection data by correcting, based on one or more pixel parameters, the scan projection data. The systems may also determine a reconstructed image by performing, based on the corrected projection data, image reconstruction. The systems may further determine density distribution images of at least two target materials of the target object by decomposing the reconstructed image.