Automatic correction of biplane projection imaging geometry.
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.
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Cedars-Sinai Medical Center, Los Angeles, California 90048, USA.
Morioka
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Whiting
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JS
D000465:Algorithms; D000792:Angiography / Q000379:methods* / Q000706:statistics & numerical data; D000818:Animals; D001699:Biometry; D055592:Biophysical Phenomena; D001703:Biophysics; D001808:Blood Vessels / Q000033:anatomy & histology*; D006801:Humans; D019047:Phantoms, Imaging; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods*; D013552:Swine