Coronary Vessel Segmentation by Coarse-to-Fine Strategy Using U-nets
Algorithm 3
Small blood vessel region detection.
Input: L: List of important nodes in the blood vessels, the central line image (skeleton binary image), label of object pixels.
Output: B: List of rectangles including small blood vessels
Step 1. Find blood vessel segments, edges
Init: edges = ∅
Visit every node of list L:
edge = ∅
Repeat
(i) Find neighbour object pixel (called as nb) of the current node (the pixel with label of 1 in the central line image),
(ii) Update: node = nb,
(iii) edge.append(node)
Until nb∈ L
edges.append(edge)
Step 2. Find the top-left and bottom-right coordinates of rectangle
Init: i =0; B = ∅
For edge edges:
(i) Find two points, p1 and p2, so that p1 is the top-left point and p2 is the bottom-right point of a rectangle that includes the largest blood vessel region based on equations (3) and (4).
