Segmentation

Author : OpenTPS team

This example will present the basis of segmentation with openTPS core. running time: ~ 5 minutes

Setting up the environment in google collab

import sys
if "google.colab" in sys.modules:
    from IPython import get_ipython
    get_ipython().system('git clone https://gitlab.com/openmcsquare/opentps.git')
    get_ipython().system('pip install ./opentps')
    get_ipython().system('pip install scipy==1.10.1')
    import opentps

imports

import numpy as np
import matplotlib.pyplot as plt
import logging
import os

import the needed opentps.core packages

from opentps.core.data.images import CTImage
from opentps.core.processing.segmentation.segmentation3D import applyThreshold
from opentps.core.processing.segmentation.segmentationCT import SegmentationCT
from opentps.core.examples.syntheticData import *

logger = logging.getLogger(__name__)

Output path

output_path = 'Output'
if not os.path.exists(output_path):
    os.makedirs(output_path)

Genrerate synthetic CT image and segment it

# GENERATE SYNTHETIC CT IMAGE
ct = createSynthetic3DCT()

# APPLY THRESHOLD SEGMENTATION
mask = applyThreshold(ct, -750)

# APPLY CT BODY SEGMENTATION
seg = SegmentationCT(ct)
body = seg.segmentBody()
bones = seg.segmentBones()
lungs = seg.segmentLungs()

# CHECK RESULTS
assert (body.imageArray[50,100,80] == True) & (body.imageArray[0,0,0] == False), f"Wrong body segmentation"
assert (bones.imageArray[85,100,50] == True) & (bones.imageArray[85,110,50] == False), f"Wrong bones segmentation"
assert (lungs.imageArray[120,100,35] == True) & (lungs.imageArray[50,100,35] == False), f"Wrong lungs segmentation"

DISPLAY RESULTS

fig, ax = plt.subplots(2, 5)
fig.tight_layout()
y_slice = 100
z_slice = 35 #round(ct.imageArray.shape[2] / 2) - 1
ax[0,0].imshow(ct.imageArray[:, y_slice, :].T[::-1, ::1], cmap='gray', origin='upper', vmin=-1000, vmax=1000)
ax[0,0].title.set_text('CT')
ax[0,1].imshow(mask.imageArray[:, y_slice, :].T[::-1, ::1], cmap='gray', origin='upper', vmin=0, vmax=1)
ax[0,1].title.set_text('Threshold')
ax[0,2].imshow(body.imageArray[:, y_slice, :].T[::-1, ::1], cmap='gray', origin='upper', vmin=0, vmax=1)
ax[0,2].title.set_text('Body')
ax[0,3].imshow(bones.imageArray[:, y_slice, :].T[::-1, ::1], cmap='gray', origin='upper', vmin=0, vmax=1)
ax[0,3].title.set_text('Bones')
ax[0,4].imshow(lungs.imageArray[:, y_slice, :].T[::-1, ::1], cmap='gray', origin='upper', vmin=0, vmax=1)
ax[0,4].title.set_text('Lungs')

ax[1,0].imshow(ct.imageArray[:, :, z_slice].T[::1, ::1], cmap='gray', origin='upper', vmin=-1000, vmax=1000)
ax[1,0].title.set_text('CT')
ax[1,1].imshow(mask.imageArray[:, :, z_slice].T[::1, ::1], cmap='gray', origin='upper', vmin=0, vmax=1)
ax[1,1].title.set_text('Threshold')
ax[1,2].imshow(body.imageArray[:, :, z_slice].T[::1, ::1], cmap='gray', origin='upper', vmin=0, vmax=1)
ax[1,2].title.set_text('Body')
ax[1,3].imshow(bones.imageArray[:, :, z_slice].T[::1, ::1], cmap='gray', origin='upper', vmin=0, vmax=1)
ax[1,3].title.set_text('Bones')
ax[1,4].imshow(lungs.imageArray[:, :, z_slice].T[::1, ::1], cmap='gray', origin='upper', vmin=0, vmax=1)
ax[1,4].title.set_text('Lungs')

plt.savefig(os.path.join(output_path, 'Example_Segmentation.png'))

print('Segmentation example completed')
plt.show()

Segmentation example completed