X-ray or gamma ray systems or devices – Specific application – Computerized tomography
Reexamination Certificate
2000-10-13
2003-01-07
Bruce, David V. (Department: 2882)
X-ray or gamma ray systems or devices
Specific application
Computerized tomography
C378S015000, C378S901000
Reexamination Certificate
active
06504892
ABSTRACT:
FIELD OF THE INVENTION
The present invention is directed to a system and method for reconstruction of images from cone beam volume computed tomography (CBVCT) and more particularly to such a system and method in which the data are taken over an orbit having a circle and two or more arcs.
DESCRIPTION OF RELATED ART
Among all possible applications of the Radon transform, computed tomography (CT) applied in 2-D medical and non-destructive test imaging technology may be the one that has achieved the greatest success. Recognizing the demand for saving scan time in the currently available 2-D CT and consequently greatly improving its functionality, the implementation of CBVCT has been investigated for the past two decades.
The intermediate function derived by Grangeat (P. Grangeat, “Mathematical Framework of Cone Beam 3D Reconstruction via the First Derivative of the Radon Transform,”
Mathematical Methods in Tomography, Lecture Notes in Mathematics
1497, G. T. Herman et al, eds., New York: Springer Verlag, 1991, pp. 66-97) establishes a bridge between the projection of a 3-D object and its 3-D Radon transform and is much more numerically tractable than previously known intermediate functions. With the progress in understanding the so-called data sufficiency condition for an exact reconstruction, a few cone beam non-planar scanning orbits, such as dual orthogonal circles, helical, orthogonal circle-and-line, non-orthogonal dual-ellipse, orthogonal circle-plus-arc, and even general vertex path have been proposed. Correspondingly, the analytic algorithms to exactly reconstruct a 3-D object based upon those non-planar scanning orbits have also been presented.
Generally, a cone beam filtered back-projection (FBP) algorithm can make cone beam reconstruction much more computationally efficient and more easily implemented in a multi-processor parallel computing structure. Hence, an FBP cone beam reconstruction algorithm is desirable in practice, and Feldkamp's algorithm (L. A. Feldkamp, L. C. Davis, and J. W. Kress, “Practical cone-beam algorithm,”
J. Opt. Soc. Am. A
, Vol. 1, pp. 612-619, 1984) for the circular orbit is the earliest example. Obviously, Feldkamp's algorithm violates the data sufficiency condition, and an accurate reconstruction without intrinsic artifacts is available only in the central plane overlapping the circular orbit plane, so that some accuracy on the off-central planes has to be sacrificed. Although proposed independently, many algorithms of the prior art featured a common structure of shift variant filtering (SVF) followed by cone beam back-projection. Only 1-D ramp filtering is employed in Feldkamp's algorithm, but a cascade of 2-D operations, such as weighting, 2-D projection, differentiation and 2-D back-projection, are involved in the shift variant filtering. The complexity of the SVF (O(N
4
) ) is higher than that of the 1-D ramp filtering of Feldkamp's algorithm (O(N
3
logN) ). Another important common feature possessed by many algorithms of the prior art is a normalized redundancy function (NRF) adopted to compensate for the multiple intersections of the projection plane with the source trajectory. Recently, that kind of algorithm has been extended to a more general situation in which an arbitrary vertex path is involved as long as the data sufficiency condition is satisfied. Apparently, the NRF is data-acquisition-orbit-dependent and has discontinuities in data acquisition orbits which meet the data sufficiency condition, but it can be analytically calculated for either a specific data acquisition orbit or even an arbitrary vertex path. On the other hand, the algorithm by Hu (H. Hu, “A new cone beam reconstruction algorithm for the circle-and-line orbit,”
Proceedings of International Meeting on Fully
3
D Image Reconstruction in Radiology and Nuclear Medicine
, pp. 303-310, 1995; and H. Hu, “Exact regional reconstruction of longitudinally-unbounded objects using the circle-and-line cone beam tomographic system,”
Proc. SPIE
, Vol. 3032, pp. 441-444, 1997) for an orthogonal circle-plus-line orbit is promising in saving computation resource, since a window function, instead of the NRF, is employed for the cone beam reconstruction from the projection data acquired along the line orbit.
Due to mechanical feasibility, a circular x-ray source trajectory is still the dominant data acquisition geometry in all commercial 2-D/3-D CT systems currently available. Based upon a circular source trajectory, a number of data acquisition orbits can be implemented by either moving the table or tilting the CT gantry. An orthogonal circle-plus-arc orbit has been presented. It possesses advantages that can not be superseded by other “circle-plus” geometries, especially in the application of image guided interventional procedures requiring intraoperative imaging, in which the movement of a patient table is to be avoided. Further, it can be easily realized on a C-arm-based imaging system, which is being used more and more for tomography in recent years. The orthogonal circle-plus-arc orbit can be realized by acquiring one set of 2-D cone beam circle projections while rotating an x-ray source and a 2D detector on a circular gantry and then acquiring another set of 2-D cone beam arc projections while tilting the gantry along an arc which is orthogonal to and coincident with the circular orbit at the same radius. The exact CBVCT reconstruction algorithm associated with that circle-plus-arc orbit is not in the FBP form. The rebinning process involved in the algorithm requires storage for all information in the Radon space, and makes the CBVCT reconstruction computationally inefficient. Further, the arc sub-orbit provides information covering its Radon sub-domain only once, but the circular sub-orbit provides information covering its Radon sub-domain twice. That unbalanced coverage in the Radon space may result in non-uniformity of noise characteristic in reconstructed images.
A particular application of the present invention is in the detection of lung cancer and other malignancies. CT scanning plays a central role in much of the thoracic imaging used in detection of lung cancer and other malignancies. CT is non-invasive, easy to perform, and usually straightforward to interpret. It is either the primary modality or the referral modality for the detection of pulmonary masses (primary and metastatic), non-invasive staging of primary bronchogenic carcinoma, and for detection of major complications of malignancies, particularly pulmonary emboli, and infections. However, present helical CT has three major technical shortcomings. First, helical CT scans require a long or multiple breath holds for whole lung imaging, depending on slice thickness. Second, slice thickness vs. coverage vs. scan time tradeoff: programming thinner slices increases scan time or decreases coverage. The spatial resolution is not isotropic; through plane resolution is limited by slice thickness and a few times lower than that of in-plane. Third, the clinically achievable in-plane resolution for a large FOV, such as whole lung imaging, is limited and less than or equal to 1.0 lp/mm.
CT of the chest is a potential screening tool for lung carcinoma. While screening programs based on conventional x-rays had poor sensitivity and diagnosed most carcinomas after the window of surgical cure had passed, CT scans reveal nodules below 1 centimeter with higher potential cure rates. A drawback of screening CT is poor specificity. Benign sub-centimeter nodules are common (non-calcified granulomas, intrapulmonary lymph nodes, focal regions of atelectasis). The best diagnostic algorithm post-discovery of sub-centimeter nodules is unclear. Universal resection seems impractical. Potential diagnostic algorithms include evaluating the nodule enhancement, border characteristics, and growth. In all of these cases, accurate depiction of a small nodule is necessary. Helical CT, while readily detecting these nodules, has partial volume averaging problems in accurate characterization. It would therefore be desirable
Blank Rome Comisky & McCauley LLP
Bruce David V.
University of Rochester
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