Masks

Biomedical Image Analysis in Python

Stephen Bailey

Instructor

Raw image

FullBrain

Image mask

Mask

Creating masks

Logical operations result in True / False at each pixel

mat = np.array([[1, 2, 3],
                [4, 5, 6],
                [7, 8, 9]])

mat > 5

np.array([[False, False, False],
          [False, False, True ],
          [True,  True,  True ]])

Sample Operations

hist=ndi.histogram(im, 0, 255, 256)

mask1 = im > 32

foot-histogram

foot mask 1

mask2 = im > 64

mask3 = mask1 & ~mask2

foot mask 2

foot mask 1 and 2

np.where(condition, x, y) controls what data passes through the mask.

import numpy as np

im_bone = np.where(im > 64, im, 0)

plt.imshow(im_bone, cmap='gray')
plt.axis('off')
plt.show()

image-with-non-bone-removed

m = np.where(im > 64, 1, 0)

foot mask 1

ndi.binary_dilation(m,iterations=5)

foot mask binary dilation

ndi.binary_erosion(m,iterations=5)

foot mask binary erosion

Biomedical Image Analysis in Python