X-ray or gamma ray systems or devices – Specific application – Computerized tomography
Reexamination Certificate
2001-10-30
2003-06-03
Bruce, David V. (Department: 2882)
X-ray or gamma ray systems or devices
Specific application
Computerized tomography
C378S008000, C378S901000
Reexamination Certificate
active
06574297
ABSTRACT:
BACKGROUND
1. Technical Field
The present invention relates generally to a system and method for 3-dimensional (3D) image reconstruction in a spiral scan cone beam computed tomography (CT) imaging system and, more specifically, to a spiral scan cone beam CT system and method that accurately reconstructs an image of a ROI (region of interest) within a long object by removing components associated with data contamination.
2. Description of Related Art
A system employing cone beam geometry has been developed for three-dimensional (3D) computed tomography (CT) imaging that comprises a cone beam x-ray source and a 2D area detector. An object to be imaged is scanned, preferably over a 360 degree angular range and along its entire length, by any one of various methods wherein the position of the area detector is fixed relative to the source, and relative rotational and translational movement between the source and object provides the scanning (irradiation of the object by radiation energy). The cone beam approach for 3D CT has the potential to achieve 3D imaging in both medical and industrial applications with improved speed, as well as improved dose utilization when compared with conventional 3D CT apparatus (i.e., a stack of slices approach obtained using parallel or fan beam x-rays).
As a result of the relative movement of the cone beam source to a plurality of source positions (i.e., “views”) along the scan path, the detector acquires a corresponding plurality of sequential sets of cone beam projection data (also referred to herein as cone beam data or projection data), each set of cone beam data being representative of x-ray attenuation caused by the object at a respective one of the source positions.
Various methods have been developed for 3D image reconstruction for cone beam x-ray imaging systems. For example, a filtered backprojection (FBP) cone beam image reconstruction technique is described by Kudo, H. and Saito, T., in their article entitled “Derivation and Implementation of a Cone-Beam Reconstruction Algorithm for Nonplanar Orbits”, IEEE Trans.Med, Imag., MI-13 (1994) 196-211.
Briefly, the FBP technique comprises the following steps at each cone beam view (i.e., at each position of the radiation source as it scans about the object, and at which an imaging detector acquires a corresponding set of projection data):
1. Compute a 1-dimensional projection (i.e., line integral) of the measured cone beam image acquired on a detector plane
1
at each of a plurality of angles
2
. This step is illustrated by
FIG. 1A
for a given angle
2
1
of a plurality of angles
2
, where the projection
2
at coordinates (r, 2) comprises the integrated values of the cone beam image
4
on detector plane
1
along a plurality of parallel lines L(r, 2) that are normal to angle
2
, each line L being at an incremental distance r from an origin O. Generally, if the detector plane
1
comprises an N by N array of pixels, then the number of angles
2
is typically given by BN/2.
2. Filter each 1D projection in accordance with a d/dr filter, resulting in a new set of values at each of the r, 2 coordinates, such as shown by filtered projection
6
for the angle
2
1
in FIG.
1
A.
3. Normalize the filtered projections with a normalization function M(r, 2). Normalization is needed to take into account the number of times the plane of integration Q(r, 2) which intersects the source position and the line L(r, 2), intersects the scan path, since the data developed at each scan path intersection creates a contribution to the image reconstruction on the plane Q(r, 2).
4. Backproject the filtered projection
6
from each angle
2
into a 2D object space
7
that coincides with the detector plane
1
. This step is illustrated by
FIG. 1B
, wherein lines 8 spread the value from each r, 2 coordinate into 2D space
7
in a direction normal to each 2.
5. Perform a 1D d/dt filtering of the backprojection image formed in 2D space
7
by step 4. The 1D filtering is performed in the direction of the scan path, i.e., along lines
10
, where the arrowhead points in the direction of the scan path.
6. Perform a weighted 3D backprojection of the resulting data in 2D space
7
(i.e., from each pixel in the detector) onto a plurality of sample points P in a 3D object volume
12
. The density assigned to each point P is weighted by the inverse of the square of the distance between the point and the spatial coordinates of the x-ray source (see Equation (59) of the forenoted Kudo et al article).
The above procedure will be referred to hereinafter as the 6-step process. It is assumed in this process that the entire cone beam image of the object is captured on the detector of the imaging system. Consider a plane Q(r, 2), which intersects the object, formed by the source and the line L(r, 2) on the detector at angle
2
and at a distance r from the origin. Ignoring the function M(r, 2), the operations
1
through
6
compute the contribution to the reconstructed object density on the plane Q(r, 2) from the x-ray data illuminating the plane and its immediate vicinity. Since the 6-step process is detector driven, a contribution from the data illuminating the plane is computed every time the plane intersects the scan path and thus is illuminated by the x-ray beam. Consequently, the function M(r, 2) is used after the filter function in step
2
to normalize the results. Normalization is particularly undesirable since it requires pre-computing and storing a 2D array M(r, 2) for each source position along an imaging scan path. Since there are usually hundreds, if not thousands of source positions, this type of normalization is both computationally intensive and resource (computer memory) expensive.
As well known, and fully described for example in U.S. Pat. No. 5,257,183 entitled: METHOD AND APPARATUS FOR CONVERTING CONE BEAM X-RAY PROJECTION DATA TO PLANAR INTEGRAL AND RECONSTRUCTING A THREE-DIMENSIONAL COMPUTERIZED TOMOGRAPHY (CT) IMAGE OF AN OBJECT, issued Oct. 26, 1993, incorporated herein by reference, one known method of image reconstruction processing generally begins by calculating Radon derivative data from the acquired cone beam data. The Radon derivative data is typically determined by calculating line integrals for a plurality of line segments L drawn in the acquired cone beam data. In the embodiment described in detail in the U.S. Pat. No. 5,257,183 patent, Radon space driven conversion of the derivative data is used to develop an exact image reconstruction of a region-of-interest (ROI) in the object.
A cone beam data masking technique which improves the efficiency of the calculation of the Radon derivative data in such a Radon space driven technique is described in U.S. Pat. No. 5,504,792 entitled METHOD AND SYSTEM FOR MASKING CONE BEAM PROJECTION DATA GENERATED FROM EITHER A REGION OF INTEREST HELICAL SCAN OR A HELICAL SCAN, issued Apr. 2, 1996, also incorporated herein by reference. The masking technique facilitates efficient 3D CT imaging when only the ROI in the object is to be imaged, as is normally the case. In the preferred embodiment described therein, a scanning trajectory is provided about the object, the trajectory including first and second scanning circles positioned proximate the top and bottom edges, respectively, of the ROI, and a spiral scanning path is connected therebetween. The scanning trajectory is then sampled at a plurality of source positions where cone beam energy is emitted toward the ROI. After passing through the ROI the residual energy at each of the source positions is acquired on an area detector as a given one of a plurality of sets of cone beam data. Each set of the cone beam data is then masked so as to remove a portion of the cone beam data that is outside a given sub-section of a projection of the ROI in the object and to retain cone beam projection data that is within the given sub-section. The shape of each mask for a given set of cone beam data is determined by a projection onto the detector of the scan path which is above and below the source position which acquired the given
Bruce David V.
F. Chau & Associates LLP
Paschburg Donald B.
Siemens Corporate Research Inc.
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