3D Augmentation module examples

A module implemented for the purpose of augmenting 3D volumes.
This class uses transformations in SimpleITK library to perform augmentations.

from augmentation3DUtil import Augmentation3DUtil
from augmentation3DUtil import Transforms
import SimpleITK as sitk
import matplotlib.pyplot as plt
%matplotlib inline

Reading image using SimpleITK module

img = sitk.ReadImage(fr"***Path to input image***")

Defining the object

au = Augmentation3DUtil(imgs,masks)
imgs : list of images (here 3D volumes) to be augmented. Same transformation will be applied to each of these volumes.
masks : Their corresponding binary segmentation masks (None if no masks to be augmented or provide them as list)

Performing single transformations

Use the Enum class Transforms for defining transforms. See examples below

Rotation

parameters probability : probability of the executing this particular transformation
degrees : degree of rotation.

au = Augmentation3DUtil([img],masks=None)
au.add(Transforms.ROTATE2D,probability = 1, degrees = 45)

imgs, augs = au.process(1)

arr = sitk.GetArrayFromImage(imgs[0][0])
augarr = sitk.GetArrayFromImage(augs[0][0][0])

plt.subplot(121)
plt.imshow(arr[10])
plt.axis('off')
plt.subplot(122)
plt.imshow(augarr[10])
plt.axis('off')

(-0.5, 383.5, 383.5, -0.5)

Rotation with specified binary segmentation masks.

parameters probability : probability of the executing this particular transformation
degrees : degree of rotation.

maskImg = sitk.ReadImage(fr"****Path to binary segmentation mask****")
au = Augmentation3DUtil([img],masks=[maskImg])
au.add(Transforms.ROTATE2D,probability = 1, degrees = 45)

imgs, augs = au.process(1)

arr = sitk.GetArrayFromImage(imgs[0][0])
augarr = sitk.GetArrayFromImage(augs[0][0][0])
maskarr = sitk.GetArrayFromImage(imgs[1][0])
maskaugarr = sitk.GetArrayFromImage(augs[0][1][0])


fig = plt.figure(figsize=(10,10))
plt.subplot(221)
plt.imshow(arr[10])
plt.axis('off')
plt.subplot(222)
plt.imshow(augarr[10])
plt.axis('off')
plt.subplot(223)
plt.imshow(maskarr[9])
plt.axis('off')
plt.subplot(224)
plt.imshow(maskaugarr[9])
plt.axis('off')

(-0.5, 383.5, 383.5, -0.5)

Flip horizontal

parameters probability : probability of the executing this particular transformation

au = Augmentation3DUtil([img],masks=None)
au.add(Transforms.FLIPHORIZONTAL,probability = 1)

imgs, augs = au.process(1)

arr = sitk.GetArrayFromImage(imgs[0][0])
augarr = sitk.GetArrayFromImage(augs[0][0][0])


plt.subplot(121)
plt.imshow(arr[10])
plt.axis('off')
plt.subplot(122)
plt.imshow(augarr[10])
plt.axis('off')

(-0.5, 383.5, 383.5, -0.5)

Flip vertical

parameters probability : probability of the executing this particular transformation

au = Augmentation3DUtil([img],masks=None)
au.add(Transforms.FLIPVERTICAL,probability = 1)

imgs, augs = au.process(1)

arr = sitk.GetArrayFromImage(imgs[0][0])
augarr = sitk.GetArrayFromImage(augs[0][0][0])

plt.subplot(121)
plt.imshow(arr[10])
plt.axis('off')
plt.subplot(122)
plt.imshow(augarr[10])
plt.axis('off')

(-0.5, 383.5, 383.5, -0.5)

Translation

parameters probability : probability of the executing this particular transformation
offset : 3D cordinates in mm ex. (5,5,0)

au = Augmentation3DUtil([img],masks=None)
au.add(Transforms.TRANSLATE,probability = 1, offset = (15,15,0))

imgs, augs = au.process(1)

arr = sitk.GetArrayFromImage(imgs[0][0])
augarr = sitk.GetArrayFromImage(augs[0][0][0])

plt.subplot(121)
plt.imshow(arr[10])
plt.axis('off')
plt.subplot(122)
plt.imshow(augarr[10])
plt.axis('off')

(-0.5, 383.5, 383.5, -0.5)

Shear

parameters probability : probability of the executing this particular transformation
magnitude : 3D cordinates

au = Augmentation3DUtil([img],masks=None)
au.add(Transforms.SHEAR,probability = 1, magnitude = (0.1,0.1))

imgs, augs = au.process(1)

arr = sitk.GetArrayFromImage(imgs[0][0])
augarr = sitk.GetArrayFromImage(augs[0][0][0])

plt.subplot(121)
plt.imshow(arr[10])
plt.axis('off')
plt.subplot(122)
plt.imshow(augarr[10])
plt.axis('off')

(-0.5, 383.5, 383.5, -0.5)

Random sampling of transformations (combination)

specify the number of samples to be obtained using "process" method
specify the likelihood of a particular transform as probabilities.

au = Augmentation3DUtil([img],masks=None)
au.add(Transforms.SHEAR,probability = 0.25, magnitude = (0.05,0.05))
au.add(Transforms.TRANSLATE,probability = 0.75, offset = (15,15,0))
au.add(Transforms.ROTATE2D,probability = 0.75, degrees = 10)
au.add(Transforms.FLIPHORIZONTAL,probability = 0.75)

imgs, augs = au.process(5)

for i in range(len(augs)):
    arr = sitk.GetArrayFromImage(imgs[0][0])
    augarr = sitk.GetArrayFromImage(augs[i][0][0])

    plt.subplot(121)
    plt.imshow(arr[10])
    plt.axis('off')
    plt.subplot(122)
    plt.imshow(augarr[10])
    plt.axis('off')
    plt.show()