Skip to main content
. Author manuscript; available in PMC: 2017 Jul 7.
Published in final edited form as: Phys Med Biol. 2017 Jun 12;62(13):5383–5402. doi: 10.1088/1361-6560/aa6e20
Adaptive Region-Growing with Maximum Curvature Strategy (ARG_MC) Algorithm:
V = ARG_MC (I, ROI)
Input:

  1. I: PET image;

  2. ROI: a rough rectangular region of interest manually drawn to enclose the tumor.

Set parameters:

  1. Set the discretization step Δf for the relaxing factor f: Δf = 0.1;

  2. Set the upper bound for the relaxing factor f: B = 20.

Iteration:
 For f = 0: Δf: B
   Obtain the CCRG-segmented volume at f: V(f) = CCRG(I, f, ROI);
 End
Determine ORF:

  1. Fit the f-volume curve using Eq. (2);

  2. Compute the curvature of the fitted, smoothed f-volume curve using Eq. (3);

  3. Identify the two transition points as the local MC points with the two largest curvatures;

  4. Determine ORF as the f at the first of the two transition points.

Output:
  Final segmentation V = CCRG(I, ORF, ROI).