Automatic correction of biplane projection imaging geometry

Abstract

A novel method is presented for correcting errors in measurements of biplane projection imaging geometry without prior identification of corresponding points in the two images. For imaged objects that project onto both images, a constraint equation is obtained that relates weighted integrals along corresponding epipolar lines. The integrals are computed to first order in the angular beamwidth, which is assumed to be small. Starting from measured or estimated values, geometrical parameters are computed iteratively in order to maximize the correlation between epipolar line integrals in the two images. Improvement in the computation of corresponding epipolar lines is demonstrated on images of a wire phantom. The root mean square distance of the epipolar lines from the corresponding reference points is improved from 15 pixel widths to less than 4 pixel widths (1.3 mm). Convergence is demonstrated on phantom images for individual parameter variations up to 70% in relative magnification, a relative shift of the imaging planes by 50 pixels, or a relative rotation of at least 35 degrees around either of two axes. Applicability to clinical images is demonstrated by using a biplane angiogram of a pig to align corresponding points determined from images of a Perspex cube acquired with the same geometry.

Clinical evaluation of angiographic multiple-view 3D reconstruction

“…For the biplane and pairs-of-views techniques, reliable 3D-vessel trees can be generated with the calculated magnification and orientations accurate to within approximately 1-3% and 2-5 • , respectively [10,16]. However, most of these two-view techniques [2][3][4][5][6][7][8][9][10][11][12][13][14][15][16] use corresponding points, e.g., bifurcations, and require four or more corresponding points for a determination of the imaging geometry. The two-view reconstructions can be inaccurate for end-on vessels (i.e., vessels with their centerlines parallel to the X-ray beam), for vessel segments parallel to the epipolar lines [2,3], and for inconsistencies in the 2D data [11].…”

“…To allow calculation of 3D data during interventional procedures, a number of groups have proposed self-calibrating methods based on pairs of views [6][7][8][9][10][11][12][13][14][15][16]. Self-calibrating methods make use of the image data alone and do not require a calibration object.…”

Effects of point configuration on the accuracy in 3D reconstruction from biplane images

“…Similar equations are used for the primed system. With these equations, the imaging geometry, i.e., R and t, as well as the 3D positions of the point-or line-like objects, can be determined (7)(8)(9)(10)(11)(12)(13)(14)(15)(16)(17)(18)(19).…”

“…The method used here is the enhanced Metz-Fencil technique (11)(12)(13)(14)(15)(16)(17)(18)(19). Briefly, the gantry information (right anterior-oblique/left-anterior-oblique (RAO/LAO) angles, the cranialcaudal (CC) angles, magnification, and SID of each view) are used to estimate the imaging geometry, i.e., the transformation relating the two imaging systems.…”

“…Reconstruction of 3D data from two or more views is useful for patient positioning (1-6) and vessel reconstruction (7)(8)(9)(10)(11)(12)(13)(14)(15)(16)(17)(18)(19). To generate the 3D data, the imaging system must be calibrated, i.e., the transformation relating the imaging systems must be determined.…”