["centroid_x", "centroid_y", "centroid_z", "intensity", "size"],
["position"]) #, "contrast", "ratio"])
if __name__ == '__main__':
from time import time
from copy import deepcopy
from itertools import product
from skimage.morphology import watershed, local_minima
from skimage.color import rgb2gray
import scipy.ndimage as ndi
from display_utils import display_segments_as_lines, display_solution
print("Loading a single patient... ", end="", flush=True)
t0 = time()
model_patient = Patient.build_from_folder("data/4")
print("Done. {:.4f}s".format(time() - t0))
# Splitting the background into 3 labels
model_patient.labelmaps[
"t2"].data += 2 # Adding space for the extra labels at the start
model_patient.labelmaps["t2"].data[np.logical_and(
model_patient.volumes["t2"].data < 10,
model_patient.labelmaps["t2"].data ==
2)] = 0 # posterior background is 0
model_patient.labelmaps["t2"].data[
model_patient.labelmaps["t2"].data.shape[1] //
2:, :, :][model_patient.labelmaps["t2"].data[
model_patient.labelmaps["t2"].data.shape[1] //
2:, :, :] == 0] = 1 # anterior background is 1
model_patient.labelmaps["t2"].header["num_labels"] += 2
