Spectral estimation and poly-energetic reconstruction methods and X-ray systems

Patent metadata

Field	Value
Publication number	US-10121267-B2
Application number	US-201515313239-A
Country	US
Kind code	B2
Filing date	Jun 30, 2015
Priority date	Jul 3, 2014
Publication date	Nov 6, 2018
Grant date	Nov 6, 2018

Abstract

Spectral estimation and poly-energetic reconstructions methods and x-ray systems are disclosed. According to an aspect, a spectral estimation method includes using multiple, poly-energetic x-ray sources to generate x-rays and to direct the x-rays towards a target object. The method also includes acquiring a series of poly-energetic measurements of x-rays from the target object. Further, the method includes estimating cross-sectional images of the target object based on the poly-energetic measurements. The method also includes determining path lengths through the cross-sectional images. Further, the method includes determining de-noised poly-energetic measurements and de-noised path lengths based on the acquired poly-energetic measurements and the determined path lengths. The method also includes estimating spectra for angular trajectories of a field of view based on the de-noised poly-energetic measurements and the path lengths.

First claim

What is claimed is:

1. A spectral estimation method comprising:
generating, using a plurality of poly-energetic x-ray sources, x rays; directing, using a processor, the generated x-rays towards a target object;
acquiring, by a processor, a series of poly-energetic measurements of x-rays from the target object;
estimating, by the processor, cross-sectional images of the target object based on the poly-energetic measurements;
determining, by the processor, path lengths through the cross-sectional images;
determining, by the processor, de-noised poly-energetic measurements and de-noised path lengths based on the acquired poly-energetic measurements and the determined path lengths; and
estimating, by the processor, spectra for angular trajectories of a field of view based on the de-noised poly-energetic measurements and the path lengths,

wherein estimating spectra comprises using the following iterative algorithm:

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where
Y m =de-noised poly-energetic measurements,
N M =total number of transmission measurements,
k=kth iteration,
I s =photon,
N S =total number of samplings of the spectrum, and
A m,s =system matrix element comprising the information of de-noised path lengths, material attenuation coefficients or mass attenuation coefficients and material density distribution, and spectral interval; and
reconstructing, by the processor, a volume based on the angle dependent spectra by executing the iterative algorithm, whereby executing the iterative algorithm increases reconstruction and convergence speed at the processor.

2. The spectral estimation method of claim 1 , wherein acquiring the series of poly-energetic measurements comprises acquiring the series of poly-energetic measurements which the target object is one of stationary and moving.

3. The spectral estimation method of claim 1 , further comprising positioning the target object off-center among the directed x-rays.

4. The spectral estimation method of claim 1 , further comprising applying a scatter correction algorithm for reducing scattered radiation from the target object.

5. The spectral estimation method of claim 1 , wherein estimating cross-sectional images comprises reconstructing the poly-energetic measurements, and
wherein reconstructing the poly-energetic measurements comprises using one of filtered back projection (FBP), algebraic reconstruction technique (ART), simultaneous algebraic reconstruction technique (SART), simultaneous iterative reconstruction technique (SIRT), and a statistical reconstruction algorithm to reconstruct the poly-energetic measurements.

6. The spectral estimation method of claim 1 , wherein estimating cross-sectional images comprises using a backward projection/ray-tracing technique to delineate a shape of the target object.

7. The spectral estimation method of claim 1 , wherein estimating cross-sectional images comprises registering shape and structure information of the target object to measurements.

8. The spectral estimation method of claim 1 , further comprising determining one or more of attenuation coefficients, mass attenuation coefficients, and material density distribution of at least one of material of the target object.

9. A spectral estimation system comprising:
a plurality of poly-energetic x-ray sources configured to generate x-rays and to direct the x-rays towards a target object;
detectors configured to acquire a series of poly-energetic measurements of x-rays from the target object; and
a computing device comprising a memory and processor, wherein the processor is configured to:
estimate cross-sectional images of the target object based on the poly-energetic measurements;
determine path lengths through the cross-sectional images;
determine de-noised poly-energetic measurements and de-noised path lengths based on the acquired poly-energetic measurements and the determined path lengths; and
estimate spectra for angular trajectories of a field of view based on the de-noised poly-energetic measurements and the path lengths,

wherein estimating spectra comprises using the following iterative algo

Assignees

• Univ Duke

Inventors

• Lin Yuan
• Samei Ehsan

Classifications

• G06T12/20

  Inverse problem, i.e. transformations from projection space into object space · CPC title

• G06T12/10

  Image preprocessing, e.g. calibration, positioning of sources or scatter correction · CPC title

• G06T12/30 Primary

  Image post-processing, e.g. metal artefact correction · CPC title

• G06T11/008 Primary

  Physics · mapped topic

• A61B6/482 Primary

  involving multiple energy imaging · CPC title