Robust detection of circles in the vessel contours and application to local probability density estimation

Abstract

In this work we propose a technique to automatically estimate circular cross-sections of the vessels in CT scans. First, a circular contour is extracted for each slice of the CT by using the Hough transform. Afterward, the locations of the circles are optimized by means of a parametric snake model, and those circles which best fit the contours of the vessels are selected by applying a robust quality criterion. Finally, this collection of circles is used to estimate the local probability density functions of the image intensity inside and outside the vessels. We present a large variety of experiments on CT scans which show the reliability of the proposed method.