Spatial-Spectral Filter for Multi-Material CT Decomposition
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Solution Overview
Problem
Current spectral CT systems are limited in their ability to perform multi-material decomposition due to their focus on single contrast agent imaging, often restricting them to two spectral channels, which hinders the simultaneous imaging of multiple contrast agents.
Innovation Solution
A spatial-spectral filter configured with a repeating pattern of distinct materials, such as bismuth, tungsten, and erbium, is used to shape the x-ray beam into multiple beamlets with different spectra, allowing for the decomposition of objects into various material categories, including biological materials and contrast agents, and is optimized for particular contrast agents by mechanical translation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If spectral CT systems use only two spectral channels (e.g., dual-source, kV-switching, split-filters), then the system complexity is reduced and ease of operation is improved, but the ability to perform multi-material decomposition and simultaneous imaging of multiple contrast agents is limited
Solution Approach 1:
The filter is segmented into multiple discrete filter elements (e.g., 3-5 different materials) arranged in a repeating pattern across the beam path. Each filter element creates a distinct spectral channel, enabling multi-material decomposition without requiring multiple x-ray sources or complex detector systems. This segmentation approach increases spectral channel count from 2 to 3-5 while maintaining system simplicity.
Solution Approach 2:
Instead of increasing spectral channels by adding more x-ray sources (temporal dimension) or detector layers (spatial dimension), the invention uses a spatial-spectral filter that varies filter material composition across the beam path. This creates spectral diversity in the spatial domain, allowing multiple spectral channels to be generated simultaneously from a single source-detector pair.
2Measurement precision
If spectral CT systems are optimized for single contrast agent imaging, then the imaging quality for that specific agent is improved, but the flexibility to image multiple contrast agents simultaneously is reduced
Solution Approach 1:
The spatial-spectral filter with multiple filter elements (e.g., aluminum, copper, tungsten, bismuth) creates a universal spectral sampling approach that can characterize multiple contrast agents simultaneously. The repeating filter pattern ensures that all spectral channels are available across the entire field of view, enabling flexible imaging of iodine, gadolinium, bismuth, and other contrast agents without system reconfiguration.
Solution Approach 2:
The filter design allows adjustment of filter element materials, thicknesses, and patterns to optimize spectral sampling for different contrast agents. By changing the filter parameters (material composition, thickness distribution), the system can be adapted to image various contrast agents with different attenuation characteristics while maintaining multi-material decomposition capability.
3Measurement precision
If more spectral channels are used for multi-material decomposition, then the material decomposition accuracy is improved, but the data acquisition complexity and processing requirements increase
Solution Approach 1:
The spatial-spectral filter passively generates multiple spectral channels through its material composition and geometry, without requiring active modulation of the x-ray source or complex detector readout schemes. The filter structure itself serves the function of spectral shaping, reducing the complexity of data acquisition while providing 3-5 spectral channels for accurate material decomposition.
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
This approach enables the collection of multiple spectral channels, facilitating multi-material decomposition with improved sampling patterns and density estimation, enhancing the imaging capabilities for multiple contrast agents while maintaining flexibility in data acquisition.
Implementation Method 1
The spatial-spectral filter is configured to spectrally shape a beam into a number of beamlets with different spectra. The spatial-spectral filter is formed from at least two distinct materials. The at least two distinct materials are alternated to form a repeating pattern of materials.
Data Source
AI summary
The present invention is directed to spatial-spectral filtering for multi-material CT decomposition. The invention includes a specialized filter that spectrally shapes an x-ray beam into a number of beamlets with different spectra. The filter allows decomposition of an object/anatomy into different material categories (including different biological types: muscle, fat, etc. or exogenous contrast agents that have been introduced: e.g iodine, gadolinium, etc.). The x-ray beam is spectrally modulated across the face of the detector using a repeating pattern of filter materials. Such spatial-spectral filters allow for collection of many different spectral channels using “source-side” control. However, in contrast to other spectral techniques that provide mathematically complete projection data, spatial-spectral filtered data is sparse in each spectral channel—making traditional projection-domain or image-domain material decomposition difficult to apply. Therefore, the present invention uses model-based material decomposition, which combines reconstruction and multi-material decomposition, and permits arbitrary spectral, spatial, and angular sampling patterns.