Material decomposition of multi-spectral x-ray projections using neural networks
AssigneeMarquette University
InventorsTal Gilat Schmidt, Kevin C. Zimmerman
Life of this patent
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Abstract
A method of processing x-ray images comprises training an artificial neural network to process multi-spectral x-ray projections to determine composition information about an object in terms of equivalent thickness of at least one basis material. The method further comprises providing a multi-spectral x-ray projection of an object, wherein the multi-spectral x-ray projection of the object contains energy content information describing the energy content of the multi-spectral x-ray projection. The multi-spectral x-ray projection is then processed with the artificial neural network to determine composition information about the object, and then the composition information about the object is provided.
Claims21
A method of processing x-ray images, the method comprising:
- training an artificial neural network to process multi-spectral x-ray projections to determine composition information in terms of equivalent thickness of at least one basis material;
- providing a multi-spectral x-ray projection of an object, wherein the multi-spectral x-ray projection of the object contains energy content information describing energy content of the multi-spectral x-ray projection;
- processing the multi-spectral x-ray projection with the artificial neural network to determine composition information about the object, wherein the composition information includes one or more basis coefficients mapping the object in terms of equivalent thicknesses of the at least one basis material;
- and
- providing the composition information about the object.
A method of imaging an object comprising:
- projecting multi-spectral x-ray beams through an object;
- detecting a multi-spectral x-ray projection through the object, wherein the detecting includes detecting the energy content of the multi-spectral x-ray beams;
- and
- processing the multi-spectral x-ray projection with an artificial neural network to determine composition information about the object, wherein the composition information includes a set of basis coefficients mapping the object in terms of equivalent thickness of at least one basis material.
A system for imaging an object, the system comprising:
- an imaging device configured to produce a multi-spectral x-ray image of an object;
- and
- an artificial neural network trained to process the multi-spectral x-ray image to produce composition information;
- wherein the neural network is trained by providing a set of calibration x-ray projections of known thicknesses of at least one basis material as input to the neural network and utilizing a training algorithm to minimize the error between the composition information and the known thicknesses;
- and
- wherein the composition information includes an array of basis coefficients mapping the object in terms of equivalent thicknesses of the at least one basis material.
Dependencies are inferred from the claim text.