Coronary Vessel Segmentation by Coarse-to-Fine Strategy Using U-nets

Algorithm 2

Detecting important nodes in the blood vessel tree.

Input: The central line of the large vessel segmentation result (output central line)

Output: L: List of important nodes in the blood vessels

Step 1. Based on the image of the central line of a large vessel (binary image), we classify each pixel () into three classes (three labels) [0, 1, 2] as follows:

Step 2. Find the important nodes (start, end, and junction nodes)

While output central line (skeleton image) and ==2:

 + Find neighbour object pixels of pixel that were classified into class 2 (label 2), and then calculate centroid point of them.

 + node ← centroid point

 + L.append(node) (add determined node into List L)

End