CT Spectral Calibration via Table Contribution Subtraction
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Solution Overview
Problem
As CT systems increase scan coverage, calibration phantoms grow in size, making spectral calibration difficult due to their increased weight and size, particularly when positioned at the edge of the patient table.
Innovation Solution
A method involving acquiring air scans and phantom scans at various peak voltages and filters, processing projections to remove non-phantom components, and deriving spectral calibration vectors by calculating deviation ratios, allowing calibration even with phantoms positioned on the patient table.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If the scan coverage of CT systems is increased, then the imaging capability is improved, but the calibration phantom size and weight increase making spectral calibration difficult
Solution Approach 1:
The calibration process is segmented into multiple steps: acquiring projections with the phantom on the table, removing table contributions through subtraction, and deriving calibration coefficients from the cleaned data. This segmentation allows calibration of large phantoms without requiring them to be positioned at the table edge.
Solution Approach 2:
Table contributions are extracted and removed from the projection data through subtraction of table-only projections from phantom-on-table projections. This extraction isolates the phantom signal from the table interference, enabling accurate calibration even when the phantom remains on the table.
2Measurement precision
If large phantoms are positioned at the edge of the patient table for calibration, then spectral calibration can be performed, but the operation becomes increasingly difficult
Solution Approach 1:
An intermediary computational process is introduced: table contribution removal through projection subtraction. This intermediary step mediates between the practical constraint of keeping the phantom on the table and the requirement for accurate calibration data, eliminating the need to position the phantom at the table edge.
3Area of stationary object
If calibration phantoms are made larger to cover increased scan coverage, then the calibration coverage is improved, but the phantom weight and handling difficulty increase
Solution Approach 1:
The mechanical approach of positioning large phantoms at the table edge is replaced with a computational approach: acquiring projections with the phantom on the table, removing table contributions through subtraction, and deriving calibration coefficients. This substitution eliminates the need to manually position heavy phantoms while maintaining calibration accuracy.
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 effective spectral calibration of CT systems by removing table contributions from calibration data and deriving accurate calibration vectors, facilitating the correction of beam hardening and scatter-induced artifacts without requiring precise phantom centering.
Implementation Method 1
an X-ray source emits radiation (e.g., X-rays) towards an object or subject... The emitted X-rays, after being attenuated by the subject or object, typically impinge upon an array of radiation detector elements
Data Source
AI summary
The present disclosure relates to the performing spectral calibration of a CT imaging system. In accordance with certain embodiments, spectral calibration phantoms are scanned while positioned on a table in the imaging volume of the CT imaging system. The scans of the calibration phantoms, in conjunction with air sans performed on the CT imaging system, are used to derive information about the deviation of the measured phantom scans from an ideal. The deviation information is in turn used to derive spectral calibration vectors that may be used with the CT imaging system.