An Unbiased Technique For Automatic Estimation Of Vessel Contours In Angiograms

Accurate and fully automatic assessment of artery dimensions in angiograms has been sought as a diagnostic tool, in particular for coronary heart disease. We propose a new technique to estimate vessel borders in an-giographic images. Unlike in previous approaches, the obtained edge estimates are unbiased, this being of primordial importance since quantitative analysis is the goal. Another important feature of the proposed estimator is that no con-stant background is assumed, making it well suited for noxi-subtracted angiograms. The key aspect of our approach is that the smoothness constraint is not used to smooth or in some other way modify the estimates directly derived from the image (which would introduce bias) but rather elect (without modifying) candidate estimates. As a result, tlie selected points, if correct, are unbiased estimates. Even at low contrast segments and in tlie vicinity of artifacts, the true border points still correspond to (possibly faint) local maxima of the edge operator, wliicli can be correctly chosen if the surrounding context is taken into account. Robustness against unknown background is provided by tlie use a morphological edge detector rather than some linear opera-tor such as a matched filter wliicli assumes flat background. I.