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 inlineimg = sitk.ReadImage(fr"***Path to input image***")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)
Use the Enum class Transforms for defining transforms. See examples below
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)
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)
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)
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)
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)
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)
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()
React
Typescript
Django
Laravel
Facebook
Microsoft
Google
Alibaba
D3
Tencent