Accurate segmentation of blood vessels from 3D medical images
The authors' work contributes to the accurate segmentation of blood vessels from 3D medical images. The blood vessel axis and surface are optimized in an alternating way. Starting from an initial blood vessel axis estimate, slices are resampled in the 3D data volume perpendicular to this axis. In these slices, blood vessel contour candidate points are extracted at maximum gradient positions on a star pattern. The selection of a closed contour among these candidates is optimized with respect to a cost function by dynamic programming. The blood vessel axis is re-estimated at the center of the extracted contours and the process is repeated until convergence. Results are shown on both synthetic and real spiral CT angiographic images.