X-ray or gamma ray systems or devices – Specific application – Computerized tomography
Reexamination Certificate
1999-09-07
2001-07-24
Bruce, David V. (Department: 2882)
X-ray or gamma ray systems or devices
Specific application
Computerized tomography
C378S015000, C378S901000
Reexamination Certificate
active
06266388
ABSTRACT:
BACKGROUND OF THE INVENTION
This invention relates generally to computed tomography and, more particularly, to reconstructing an image using data collected in a scan using a computed tomography system.
In at least one known computed tomography (CT) imaging system configuration, an x-ray source projects a fan-shaped beam which is collimated to lie within an X-Y plane of a Cartesian coordinate system and generally referred to as the “imaging plane”. The x-ray beam passes through the object being imaged, such as a patient. The beam, after being attenuated by the object, impinges upon an array of radiation detectors. The intensity of the attenuated beam radiation received at the detector array is dependent upon the attenuation of the x-ray beam by the object. Each detector element of the array produces a separate electrical signal that is a measurement of the beam attenuation at the detector location. The attenuation measurements from all the detectors are acquired separately to produce a transmission profile.
In known third generation CT systems, the x-ray source and the detector array are rotated with a gantry within the imaging plane and around the object to be imaged so that the angle at which the x-ray beam intersects the object constantly changes. A group of x-ray attenuation measurements, i.e., projection data, from the detector array at one gantry angle is referred to as a “view”. A “scan” of the object comprises a set of views made at different gantry angles, or view angles, during one revolution of the x-ray source and detector. In an axial scan, the projection data is processed to construct an image that corresponds to a two dimensional slice taken through the object. One method for reconstructing an image from a set of projection data is referred to in the art as the filtered back projection technique. This process converts the attenuation measurements from scan into integers called “CT numbers” or “Hounsfield units”, which are used to control the brightness of a corresponding pixel on a cathode ray tube display.
Cone beam scanning is performed using a multi-dimensional detector array instead of a linear detector array as is used in a fan beam scan. In a cone beam helical scan, the x-ray source and the multi-dimensional detector array are rotated with a gantry within the imaging plane as the patient is moved in the z-axis synchronously with the rotation of the gantry. Such a system generates a multi-dimensional helix of projection data. As compared to fan beam helical scanning, cone beam helical scanning provides improved slice profiles, greater partial volume artifact reduction, and faster patient exam speed.
One known algorithm for performing image reconstruction using data collected in a cone beam scan is described in Feldkamp et al., “Practical cone-beam algorithm”, J. Opt. Soc. Am. A., Vol. 1, No. 6, pp. 612-619, sometimes referred to herein as the Feldkamp algorithm. With the Feldkamp algorithm, and when objects with high density and non-uniform distribution are place off center plane (the fan beam plane), severe shading artifact may result.
BRIEF SUMMARY OF THE INVENTION
Methods and apparatus for generating an image using data collected in a cone beam scan are described. In an exemplary embodiment, a method includes the steps of reconstructing an initial image &rgr; using the collected data, and segmenting image data for the image &rgr; into a plurality of data sets. At least one of the data sets corresponds to high density objects. Then, an error image &PSgr; is generated by using the high density image data set, and a final corrected image &khgr; is generated using the initial image &rgr; and error only image &PSgr;.
In the exemplary embodiment, the error image &PSgr; is generated by generating a high density object image &zgr; using the high density image data set, and removing an original high density object image &eegr; generated from the collected data from high. density object image &zgr;. More specifically, the error image &PSgr; is generated in accordance with:
&PSgr;=&zgr;−
f
(&eegr;)
where f is a filtering function that estimates a point spread function of forward projection and reconstruction. The final corrected image &khgr; is generated by removing error only image &PSgr; from original image &rgr; in accordance with:
&khgr;=&rgr;−
g
(&PSgr;)
where g is a filtering operator for noise reduction.
REFERENCES:
patent: 5960056 (1999-09-01), Lai
Feldkamp et al., “Practical cone-beam algorithm”, J. Opt. Soc. Am. A., vol. 1, No. 6, pp. 612-619 (Jun. 1984).
Armstrong Teasdale LLP
Bruce David V.
Cabou Christian G.
General Electric Company
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