X-ray or gamma ray systems or devices – Specific application – Computerized tomography
Reexamination Certificate
1999-03-01
2001-11-20
Grant, William (Department: 2121)
X-ray or gamma ray systems or devices
Specific application
Computerized tomography
C700S098000, C700S182000
Reexamination Certificate
active
06320928
ABSTRACT:
BACKGROUND OF THE INVENTION
The invention concerns the reconstruction of a three-dimensional image of an object from a set of two-dimensional projected images of the object obtained for different positions of a camera around the object.
Its application is of particular interest in the medical field, in which reconstruction of the internal structures of a patient being examined is undertaken, and especially the reconstruction of angiographic images, that is, to obtain images of vascular trees opacified by injection of a contrast product.
The invention can, however, find applications in other fields, notably, in nondestructive industrial control, in which examinations of the same type as medical examinations are performed.
In the medical field two-dimensional projected images of the object, a patient's head, for example, are generally obtained by rotation of an X-ray camera turning around the object
There are essentially two types of reconstruction algorithms in X-ray imaging.
A first type provides for a calculation of back projection and filtering or even a reconstruction by Fourier transform in several dimensions.
A second type, involved in the present invention, concerns iterative methods of reconstruction also called algebraic. The principle of such an algebraic algorithm is well known to the expert and has already been the subject of numerous published papers. One can notably cite Gordon, Bender and Herman, “Algebraic Reconstruction Technic for Three-Dimensional Electron Microscopy and X-ray Photography,”
Journal THEO. BIOL
. 29, pages 471 to 781 (1970); Anil K. Jain, “Fundamentals of Digital Image Processing,” Prentice Hall Information and System Sciences Series, Thomas Kailath Series Edition, or French patent Applications Nos. 89 03606 or 89 16906.
After a calibration of the camera used to determine, notably, the parameters of projection in the projection planes of the acquired images, of an observed volume broken down into elementary volume elements or voxels (those calibration parameters forming projection matrices), the algebraic image reconstruction algorithm is used to reconstruct the three-dimensional volume from those two-dimensional projected images. The basic principle of the algorithm is to initialize the voxels of the volume to a predetermined initial value, a zero value, for example, and to repeat a number of times the following operations: projection of voxels in the plane of each acquired image so as to obtain a virtual image, determination of the difference between the projected volume (virtual image) and the corresponding acquired image and then back projection of the difference in volume. After a number of iterations, an estimated value representative of the density of the contrast product injected in the vessels X-rayed is obtained for each voxel, which makes it possible to visualize in three dimensions the cartography of those X-rayed vessels.
Such an algorithm necessitates determining a great number of times, typically several million times, the projection of a voxel, using the different projection matrices.
If the algorithm is not optimized, determination of the projection of a voxel requires at least nine additions, ten multiplications and one division, which is a severe drain on the calculation time of the microprocessor incorporating the algorithm and, consequently, on the duration of image reconstruction.
BRIEF SUMMARY OF THE INVENTION
An embodiment of the invention optimizes the time of calculation of the image reconstruction algorithm and consequently reduces the time necessary for reconstruction of the three-dimensional image.
An embodiment of the invention is thus intended to reduce to a single addition the number of operations necessary for the determination of projection of a current voxel, knowing the projection of the previous voxel.
An embodiment of the invention therefore proposes a method of reconstruction of a three-dimensional image of an object from a set of digital two-dimensional projected images of the object obtained for different positions of a camera around the object. The embodiment of the method may include a calibration of the camera, an acquisition of the set of digital two-dimensional projected images and a reconstruction of the three-dimensional image from the projected two-dimensional acquired images and an iterative algorithm of algebraic image reconstruction. According to a general characteristic of an embodiment of the invention, the calibration stage a volume containing the object is broken down into voxels, the space coordinates of which are identified in a so-called chosen “calibration” frame of reference. A pretreatment or rectification is applied on each acquired image in order to establish a rectified image having a predetermined spatial orientation selected as a function of a chosen specific axis of the calibration frame of reference, e.g., the mean estimated axis of rotation of the camera around the object. The iterative algorithm of algebraic image reconstruction between each rectified image and the set of voxels is then applied by successively treating the voxels in a predetermined order linked to the choice of said specific axis. The duration of reconstruction of the three-dimensional image is thus minimized.
REFERENCES:
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Parker et al, “Three-Dimensional Reconstruction and Flow Measurements of Coronary Arteries Using Multi-view Digital Angiography” New Developments in Quantitative Coronary Angiography, J.C. Riebor, P.W. Surreys, Eds. pp 225-247, Kluwor Academic Publishers, 1988.
D.J. Hawkes et al. “The Accurate 3-D Reconstruction of the Geometric Configuration of the Vascular Trees From X-Ray Recordings”, Physics And Engineering of Med/Caz Imaging, R. Guzzardi, Ed, Nijhaffi 1987.
Garremi et al. “A Knowledge-Based Approach for 3-D Reconstruction and Labeling of Vascular Networks From Biplane Angiographic Projections”, IEEE Medical Imaging, vol. 10, No. 2, pp 122-131, Jun. 1991.
Gordon et al, “Algebraic Reconstruction Techniques (ART) for Three-Dimensional Electron Microscopy and X-ray Photography”, Journal of Theo. Biol (1970) vol. 29, pp 971-981.
Fundamentals of Digital Image Processing, Jain, Sep. 1988, Engineering/Science/Mathematics.
Garcia, I et al, “Implementation and Experimental Evaluation of the Constrained Art Algorithm on a Multicomputer System,” Signal Processing, vol. 51, No. 1, May 1, 1996, pp 69-76.
Herman, G.T. et al, “Algebraic Reconstruction Techniques Can be Made Computationally Efficient”, IEEE Trans. on Medical Imaging, vol. 12, No. 3 Sep. 1, 1993, pp 600-609.
Payot et al, “An Adaptative and Constrained Model For 3D X-Ray Vascular Reconstruction”, Proceedings of the 1975 International Meeting on Fully Three Dimensional Image Reconstruction in Radiology and Nuclear Medicine, Jul. 4, 1995, France.
Boucherie Romain
Romeas Rene
Trousset Yves
Vaillant Regis
Cabrera Zoila
Chaskin Jay L.
GE Medical Systems S.A.
Grant William
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