Separate colors in immunohistochemical staining

Question

[salvatore.raieli2]

Hi everyone,

I was trying to replicate this tutorial:

https://scikit-image.org/docs/dev/auto_examples/color_exposure/plot_ihc_color_separation.html

the results should be this:

I used jupyter, spider and google colab, but the results are different.

I just copy and paste the tutorial (the libraries are correctly installed).

executing the code this my results:

do you what is happening? how to fix it? or some good tutorial/suggestion to analyze immunohistochemical staining with R or Python?

thank you for your answers

[Kevin Blighe]

Please show code that allows for us to reproduce the problem.

[salvatore.raieli2]

I just copy and paste the code present in the tutorial. I executed and it did not worked

[salvatore.raieli2]

I added in the answer the code

[salvatore.raieli2]

here is the code:

import numpy as np
import matplotlib.pyplot as plt

from skimage import data
from skimage.color import rgb2hed, hed2rgb
# Example IHC image
ihc_rgb = data.immunohistochemistry()

# Separate the stains from the IHC image
ihc_hed = rgb2hed(ihc_rgb)

# Create an RGB image for each of the stains
null = np.zeros_like(ihc_hed[:, :, 0])
ihc_h = hed2rgb(np.stack((ihc_hed[:, :, 0], null, null), axis=-1))
ihc_e = hed2rgb(np.stack((null, ihc_hed[:, :, 1], null), axis=-1))
ihc_d = hed2rgb(np.stack((null, null, ihc_hed[:, :, 2]), axis=-1))

# Display
fig, axes = plt.subplots(2, 2, figsize=(7, 6), sharex=True, sharey=True)
ax = axes.ravel()

ax[0].imshow(ihc_rgb)
ax[0].set_title("Original image")

ax[1].imshow(ihc_h)
ax[1].set_title("Hematoxylin")

ax[2].imshow(ihc_e)
ax[2].set_title("Eosin")  # Note that there is no Eosin stain in this image

ax[3].imshow(ihc_d)
ax[3].set_title("DAB")

for a in ax.ravel():
    a.axis('off')

fig.tight_layout()

from skimage.exposure import rescale_intensity

# Rescale hematoxylin and DAB channels and give them a fluorescence look
h = rescale_intensity(ihc_hed[:, :, 0], out_range=(0, 1),
                      in_range=(0, np.percentile(ihc_hed[:, :, 0], 99)))
d = rescale_intensity(ihc_hed[:, :, 2], out_range=(0, 1),
                      in_range=(0, np.percentile(ihc_hed[:, :, 2], 99)))

# Cast the two channels into an RGB image, as the blue and green channels
# respectively
zdh = np.dstack((null, d, h))

fig = plt.figure()
axis = plt.subplot(1, 1, 1, sharex=ax[0], sharey=ax[0])
axis.imshow(zdh)
axis.set_title('Stain-separated image (rescaled)')
axis.axis('off')
plt.show()