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Merge pull request #441 from spotter/color_deconv
ENH: Adding color deconvolution for immunohistochemical images.
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"""
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==============================================
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Immunohistochemical staining colors separation
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==============================================
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In this example we separate the immunohistochemical (IHC) staining
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from the hematoxylin counterstaining. The separation is achieved with the
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method described in [1]_, known as "color deconvolution".
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The IHC staining expression of the FHL2 protein is here revealed with
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Diaminobenzidine (DAB) which gives a brown color.
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.. [1] A. C. Ruifrok and D. A. Johnston, "Quantification of histochemical
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staining by color deconvolution.," Analytical and quantitative
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cytology and histology / the International Academy of Cytology [and]
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American Society of Cytology, vol. 23, no. 4, pp. 291-9, Aug. 2001.
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"""
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import matplotlib.pyplot as plt
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from skimage import data
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from skimage.color import rgb2hed
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ihc_rgb = data.immunohistochemistry()
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ihc_hed = rgb2hed(ihc_rgb)
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fig, axes = plt.subplots(2, 2, figsize=(7, 6))
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ax0, ax1, ax2, ax3 = axes.ravel()
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ax0.imshow(ihc_rgb)
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ax0.set_title("Original image")
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ax1.imshow(ihc_hed[:, :, 0], cmap=plt.cm.gray)
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ax1.set_title("Hematoxylin")
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ax2.imshow(ihc_hed[:, :, 1], cmap=plt.cm.gray)
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ax2.set_title("Eosin")
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ax3.imshow(ihc_hed[:, :, 2], cmap=plt.cm.gray)
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ax3.set_title("DAB")
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for ax in axes.ravel():
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ax.axis('off')
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fig.subplots_adjust(hspace=0.3)
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"""
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.. image:: PLOT2RST.current_figure
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Now we can easily manipulate the hematoxylin and DAB "channels":
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"""
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import numpy as np
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from skimage.exposure import rescale_intensity
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# Rescale hematoxylin and DAB signals and give them a fluorescence look
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h = rescale_intensity(ihc_hed[:, :, 0], out_range=(0, 1))
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d = rescale_intensity(ihc_hed[:, :, 2], out_range=(0, 1))
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zdh = np.dstack((np.zeros_like(h), d, h))
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plt.figure()
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plt.imshow(zdh)
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plt.title("Stain separated image (rescaled)")
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plt.axis('off')
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plt.show()
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"""
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.. image:: PLOT2RST.current_figure
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"""
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