Volume Segmentation Algorithm

Step 2: Update each function using Eq. 9.72.

Step 3: Solve Eq. 9.67 for each of n iterations to keep the signed distance function property.

Step 4: Smooth each function and remove noise.

Step 5: If steady state is not reached, then go to Step 1, else go to next slice.

Step 0 is very important since bad initialization leads to bad segmentation. Automatic seed initialization is used to speed up the process and it is also less sensitive to noise. Automatic seed initialization is to divide the image into nonoverlapped windows of predefined size. Then the average gray level is calculated and compared to the mean of each class to specify the nearest class it belongs to. A signed distance function is initialized to each window. The connectivity filter is applied to remove the nonvessel tissues. The filter exploits the fact that the vascular system is a tree-like structure.

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