Algorithm 2.

Volumetric Threshold Search

1:	Input: Integer values for upper and lower volumetric threshold bounds, maximum number of iterations max_iterations, if desired
2:	Output: Volumetric threshold volume_thresh corresponding to the global minimum distribution fitting error
3:	min_thresh = lower_bound, max_thresh = upper_bound, current_thresh = min_thresh
4:	for i=l: max_iterations do
5:	if i > 1 do
6:	current_thresh = max_thresh
7:	else do
8:	sorting_indices = sort(errors, ‘ascending’)
9:	current_thresh = round(men(threshes(sorting_indices (1)), threshes(sorting_indices (2))))
10:	end
11:	past_threshes(i) = current_thresh
12:	if past_threshes(i) = past_threshes(i−1) do
13:	break
14:	end
15:	segment image using current_thresh
16:	generate histogram of volumetric data
17:	calculate fitting_error for Gamma distribution
18:	past_errors(i) = sum(fltting_error)
19:	end