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

Algorithm 1

Vessel central line extraction from a binary image.

Input: Binary image after applying large vessel extraction-based U-net

Output: Central line of vessels (output central line)

Step 1. Remove small regions less than pixels ( ~116 pixels)

Step 2. Apply the baseline Zhang-Suen thinning algorithm to get the skeleton image,

Step 3. Reconnect the broken segments in the image

 + Find connected components in the image

 + Find the largest connected component, LCC, in the image

 + Initialize: output central line = LCC

 + For each remaining connected component (small component) in the image, do

  (i) Determine orientation (or direction) of small component to the LCC and connect each small connected component to the LCC.

  (ii) Update: output central line = LCC