X-ray or gamma ray systems or devices – Specific application – Computerized tomography
Reexamination Certificate
2003-02-18
2004-06-22
Bruce, David V. (Department: 2882)
X-ray or gamma ray systems or devices
Specific application
Computerized tomography
C378S015000, C378S094000
Reexamination Certificate
active
06754298
ABSTRACT:
BACKGROUND OF THE INVENTION
1. Field of the Invention
The present invention relates to methods for statistically reconstructing images from a plurality of transmission measurements such as scans having energy diversity and image reconstructor apparatus utilizing the method. The invention can accommodate a wide variety of system configurations and measurement noise models including X-ray CT scanners and systems that use gamma sources with multiple energies, such as some SPECT transmission scans.
2. Background Art
Tomographic images of the spatial distribution of attenuation coefficients in the human body are valuable for medical diagnosis. Most hospitals have CT scanners for producing such images. Attenuation images are also useful in a variety of scientific studies, in industry for non-destructive evaluation, and for security purposes like baggage inspection. X-ray CT scanners are also being integrated into SPECT and PET scanners to provide accurate attenuation correction for emission image reconstruction and for precise anatomical localization of the functional features seen in the emission images.
Material attenuation coefficients depend on the energy of the incident photons. In clinical X-ray CT imaging, the source of the X-ray photons, bremsstrahlung radiation, has an inherently broad energy spectrum. Each photon energy is attenuated differently by the object (body). When such transmission measurements are processed by conventional image reconstruction methods, this energy-dependent effect causes beam-hardening artifacts and compromises quantitative accuracy. To avoid these difficulties, one could employ a radioisotope source with a monoenergetic spectrum, but the practical intensity is usually much lower leading to lower SNR. Recently developed fluorescence-based X-ray sources have somewhat improved intensity but still are lower than clinical CT sources. Higher intensities are obtained from monoenergetic synchrotron sources, which are expensive currently. Many gamma-emitting radioisotopes also emit photons at several photon energies.
U.S. Pat No. 6,507,633 discloses a statistical method for reconstructing images from a single measured X-ray CT sinogram. That method was the first statistical approach to include a complete polyenergetic source spectrum model in a penalized-likelihood framework with a monotonically converging iterative algorithm. DeMan et al. in “An Iterative Maximum-Likelihood Polychromatic Algorithm for CT,”
IEEE
T
R
. M
ED
. I
M
., 20(10):999-1008, October 2001 also proposed a solution to that problem based on a somewhat different object model and an algorithm that may not be monotonically converging. When only a single sinogram (for a given polyenergetic source spectrum) is available, usually one must make some fairly strong assumptions about the object's attenuation properties to perform reconstruction. For example, one may segment the object into soft tissue and bone voxels or mixtures thereof.
The energy dependence of attenuation coefficients is an inconvenience in conventional X-ray CT. Alvarez and Macovski, as disclosed in U.S. Pat No. 4,029,963, showed how to approximate the energy dependence of attenuation coefficients in terms of a Compton scattering component and a photoelectric absorption component (or, roughly equivalently, electron density and atomic number) and how to separate these two components in the sinogram domain prior to tomographic reconstruction. The separate component images could then be combined to synthesize a displayed CT image at any energy of interest. Later enhancements included noise suppression, considerations in basis material choices, energy optimization, beam-hardening assessment and correction, algorithm acceleration, scatter correction, and evaluation of precision.
Numerous potential applications of dual-energy imaging have been explored, including rock characterization for petrochemical industrial applications, soil sample analysis in agriculture, bone mineral density measurements, bone marrow composition, adipose tissue volume determinations, liver iron concentration, explosives detection, detection of contrast agents in spinal canal, non-destructive evaluation, body composition, carotid artery plaques, and radioactive waste drums. Accurate correction of Compton scatter in X-ray CT may also benefit from dual-energy information.
More recently, there has been considerable interest in using X-ray CT images to correct for attenuation in SPECT and PET image reconstruction. In these contexts, one must scale the attenuation values in the X-ray CT images and from the X-ray photon energies to the energies of the gamma photons used in SPECT and PET imaging. Kinahan et al. in “Attenuation Correction for a Combined 3D PET/CT Scanner,” M
ED
. P
HYS
., 25(10):2046-53, October 1998 have noted that accurate scaling from X-ray to PET energies may require dual-energy X-ray CT scans. This is particularly challenging in the “arms down” mode of PET scanning. If the primary purpose of the dual-energy X-ray CT scan is PET attenuation correction (rather than diagnosis), then one would like to use low X-ray doses, resulting in the need for statistical image reconstruction methods to minimize image noise.
The conventional disadvantage of dual-energy methods is the increased scan time if two (or more) separate scans are acquired for each slice. This doubling in scan time can be avoided by methods such as alternating the source energy spectra between each projection angle or between each slice or conceivably in other arrangements. Special split detectors have also been proposed.
Prior to the 1990's, all work on dual-energy X-ray CT used the FBP reconstruction method. In the early 1990's, there were a few iterative methods published for dual-energy CT reconstruction. An iterative method to achieve beam-hardening correction and decomposition into basis materials is known. Markham and Fryar in “Element Specific Imaging in Computerized Tomography Using a Tube Source of X-Rays and a Low Energy-Resolution Detector System,” N
UCL
. I
NSTR
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ETH
., A324(1):383-8, January 1993 applied the ART algorithm. Kotzki et al. in “Prototype of Dual Energy X-Ray Tomodensimeter for Lumbar Spine Bone Mineral Density Measurements; Choice of the Reconstruction Algorithm and First Experimental Results,” P
HYS
. M
ED
. B
IOL
., 37(12):2253-65, December 1992 applied a conjugate gradient algorithm. These iterative approaches treat the problem as “finding the solution to a system of equations.” These algebraic approaches can improve the accuracy relative to FBP methods, but they do not directly address the radiation dose issue. In contrast, in statistical image reconstruction approaches, the problem is posed as finding the images that best fit the measurements according to the (possibly nonlinear) physical model and a statistical model. Proper statistical modeling can lead to lower noise images, thereby enabling reductions in X-ray dose to the patient.
Statistical approaches have been extensively investigated, particularly in the last ten years, for monoenergetic transmission measurements. Recently, Clinthorne and Sukovic have investigated iterative algorithms for dual-energy and triple-energy CT reconstruction based on a weighted least-squares approach, including object-domain constraints in the following papers:
“A Constrained Dual-Energy Reconstruction Method for Material-Selective Transmission Tomography,” N
UCl
.
INSTR
. M
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. P
HYS
.
RES
. A., 351(1):347-8, December 1994;
“Design of an Experimental System for Dual-Energy X-Ray CT,” In P
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. IEEE N
UC
. S
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. S
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.
MED
. I
M
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., Vol. 2, pp. 1021-2, 1999; and
“Penalized Weighted Least-Squares Image Reconstruction in Single and Dual-Energy X-Ray Computed Tomography,” IEEE T
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., 19(11):1075-81, November 2000.
That work assumed monoenergetic measurements. Gleason et al., in the paper “Reconstruction of Multi-Energy X-Ray Computer Tomography Images of Laboratory Mice,” IEEE T
R
. N
UC
. S
CI
., 46(2):1081-6, August 1999 hint at the need for ML solutions to the multi-ener
Brooks & Kushman P.C.
Bruce David V.
The Regents of the University of Michigan
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