Image analysis – Applications – Biomedical applications
Reexamination Certificate
1999-11-20
2002-12-31
Patel, Jayanti K. (Department: 2721)
Image analysis
Applications
Biomedical applications
C382S285000, C434S272000
Reexamination Certificate
active
06501848
ABSTRACT:
BACKGROUND OF THE INVENTION
A portion of the disclosure of this patent document contains material which is subject to copyright protection. The copyright owner has no objection to the facsimile reproduction by anyone of the patent document or the patent disclosure, as it appears in the Patent and Trademark Office patent file or records, but otherwise reserves all copyright rights whatsoever.
1. Field of the Invention
The present invention relates generally to a method for reconstructing images of vascular structures and more specifically to an improved method for three-dimensional (3-D) reconstruction of vascular structures from two two-dimensional biplane projection images and methods and structures for quantitative analysis of such a reconstructed structure.
2. Discussion of Related Art
Several investigators have reported computer assisted methods for estimation of the 3-D coronary arteries from biplane projection data. These known methods are based on the known or standard X-ray geometry of the projections, placement of landmarks, known vessel shape, and on iterative identification of matching structures in two or more views. Such methods are described in a publication entitled “3-D digital subtraction angiography”,
IEEE Trans. Med. Imag.,
vol. MI-1, pp. 152-158, 1982 by H. C. Kim, B. G. Min, T. S. Lee, et. al. and in a publication entitled “Methods for evaluating cardiac wall motion in 3-D using bifurcation points of the coronary arterial tree”,
Invest. Radiology,
January-February pp. 47-56, 1983 by M. J. Potel, J. M. Rubin, and S. A. Mackay, et al. Because the computation was designed for predefined views only, it is not suitable to solve the reconstruction problem on the basis of two projection images acquired at arbitrary and unknown relative orientations.
Another known method is based on motion and multiple views acquired in a single-plane imaging system. Such a method is described in a publication entitled “Reconstructing the 3-d medial axes of coronary arteries in single-view cineangiograms”,
IEEE Trans. MI, vol.
13, no. 1, pp. 48-60, 1994 by T. V. Nguyen and J. Sklansky uses motion transformations of the heart model. However, the motion transformations of the heart model consist only of rotation and scaling. By incorporation of the center-referenced method, initial depth coordinates, and center coordinates, a 3-D skeleton of the coronary arteries was obtained. However, the real heart motion during the contraction involves five specific movements: translation, rotation, wringing, accordion-like motion, and movement toward the center of the ventricular chamber. Therefore, the model employed is not general enough to portray the true motion of the heart, especially toward the end-systole.
Knowledge-based or rule-based systems have been proposed for 3-D reconstruction of coronary arteries by use of a vascular network model. One such knowledge-based system is described in a publication entitled “An expert system for the labeling and 3-D reconstruction of the coronary arteries from two projections”,
International Journal of Imaging,
Vol. 5, No. 2-3, pp. 145-154, 1990 by Smets, Vandewerf, Suctens, and Oosterlinck. Because the rules or knowledge base were organized for certain specific conditions, it does not generalize the 3-D reconstruction process to arbitrary projection data. In other knowledge-based systems, the 3-D coronary arteries were reconstructed from a set of X-ray perspective projections by use of an algorithm from computed tomography. Due to the motion of the heart and only a limited number of projections (four or six), accurate reconstruction and quantitative measurement are not easily achieved.
Closed-form solutions of the 3-D reconstruction problem using a linear approach was a significant development and is described in, for example, a publication entitled “Determining 3-d motion and structure of a rigid body using the spherical projection”,
CVGIP,
vol. 21, pp. 21-32, 1983 by B. L. Yen and T. S. Huang. Unfortunately, actual data is always corrupted by noise or errors and the linear approach based techniques may not be sufficiently accurate when using noisy data. Hence, optimal estimation has been explicitly investigated. Additionally, U.S. Pat. No. 4,875,165 entitled Method for Determination of 3-D Structures in Biplane Angiography issued in the name of Fencil et al. also has significant drawbacks.
Use of a two-step method is known for producing an optimal estimation for a 3-D structure based on maximum-likelihood and minimum-variance estimation. In these techniques, for example, two publications entitled “Optimal motion and structure estimation”, IEEE Trans. on PAMI, Vol. 15, no. 9, September 1993, pp. 864-884, and “Structure from motion using the reconstruction and projection technique”, Proc. IEEE Workshop Computer Vision, November 1987, pp. 345-348, image error was employed in the objective function for a non-constricted minimization process. Preliminary estimates computed by a linear algorithm were used as initial estimates for the process of optimal estimation. However, if the initial solution from the linear approach is not sufficient, (e.g., with more than 2 pixels=0.6 mm error in the input 2-D image data), the iterative minimization process at the second step may become trapped in a local minimum due to a lack of prior information concerning the variables to be optimized.
Quantitative coronary analysis (“QCA”) of a reconstruction of an arterial tree was known and developed in the 1970's to quantify vessel geometry and the effects of drugs on the regression and progression of coronary artery disease. In the mid-1980's, digital systems were introduced into the catheterization laboratory to support the angiographer during the interventional procedures. With the advent digital angiographic technology, on-line QCA has been widely used predominantly for the selection of the optimal sizes of the interventional devices, and for the assessment of the efficacy of the procedure. However, current QCA techniques are performed on the 2-D projection views in which the vessel overlap and foreshortening are subjectively minimized in a “trial-and-error” manner by the interventionist. FIGS.
56
(
a
)-(
d
) demonstrate the problems resulting from use of such 2-D projections in QCA techniques.
FIG. 56
c
is an RCA image as known in the art used for QCA and resulting in a 30% narrowing measurement as shown in
FIG. 56
d.
With 2-D projection views there is no way to know or estimate how much error occurs in the QCA process due to foreshortening with respect to the stentotic segment. In
FIGS. 56
a
and
56
b,
the same vessel segment between two bifurcation points as marked by two dots at its proximal and distal ends depicts 77% and 52% foreshortening, respectively.
It is evident from the above discussion that a need exists for improved reconstruction of 3-D images from 2-D image data and that a further need exists for improved QCA techniques utilizing such 3-D reconstruction to provide needed analysis in the intervention process.
SUMMARY OF THE INVENTION
The disadvantages of present methods known for visual reconstruction of vascular structures are substantially overcome with the present invention by providing a novel method for three-dimensional reconstruction of vessels using two-dimensional angiograms and further by providing improved QCA techniques utilizing such 3-D reconstructions of vascular structures.
This patent application teaches the methods and structures of the invention with reference to vascular structures (i.e., coronary arteries or coronary arterial trees). Those skilled in the art will readily recognize that the improved reconstruction methods and the quantitative analysis methods and structures are equally applicable to any vascular structure. References herein to “coronary” or “arterial” applications of the invention are intended merely as exemplary of common vascular structures where such reconstruction and analysis techniques are beneficially applied. Nothing in this patent application should be construed as limiting
Carroll John
Chen Shiuh-Yung James
Fishman Daniel N.
Lathrop & Gage L.C.
Patel Jayanti K.
University Technology Corporation
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