Lightness Correction for Color-Coded FA Maps

To install the necessary prerequisites for this tool:

pip install ipython[all]
pip install scikit-image
pip install seaborn

Import the required packages



In [1]:

    
%matplotlib inline
import matplotlib.pyplot as plt
import seaborn as sns
import warnings
from skimage import io, color

Read the FAM and CFAM from PNG images, remove alpha channel.



In [2]:

    
fam = io.imread("fam.png")
fam_norm = fam.astype(float) / 255
cfam = io.imread("cfam.png")[:, :, 0:3]
cfam_lab = color.rgb2lab(cfam)
cfam_lightness = cfam_lab[:, :, 0].astype(float) / 100

Inject the FA values from the FAM into the L* channel of the CIE L*a*b* representation of the CFAM to get the LCFAM



In [3]:

    
lcfam_lab = cfam_lab
lcfam_lightness = fam_norm * 100
lcfam_lab[:, :, 0] = lcfam_lightness
lcfam = color.lab2rgb(lcfam_lab)

Save the resulting lightness corrected FA map to lcfam.png. Note that some loss of precision is to be expected here since all conversions were done on 64 bit floating point numbers but PNG only stores 8 bit of information in each color channel.



In [4]:

    
warnings.simplefilter("ignore")
io.imsave("lcfam.png", lcfam)

Load the LCFAM's L* channel from the resulting PNG file to visualise the difference between LCFAM L* and then input FAM. This will be slightly different from the original lcfam_lightness computed above due to the precision loss in saving mentioned above.



In [5]:

    
lcfam_lightness = color.rgb2lab(io.imread("lcfam.png")[:, :, 0:3])[:, :, 0]

Visualize the results in a single figure environment



In [6]:

    
fig, axes = plt.subplots(3, 2, figsize=(20, 20))

axes[0, 0].imshow(cfam)
axes[0, 0].axis("off")
axes[0, 0].set_title("FreeSurfer FA Map (CFAM)", fontsize=18)

axes[0, 1].imshow(lcfam)
axes[0, 1].axis("off")
axes[0, 1].set_title("Lightness Corrected FA Map (LCFAM)", fontsize=18)

axes[1, 0].imshow(cfam_lightness, cmap="gray")
axes[1, 0].axis("off")
axes[1, 0].set_title("Lightness of CFAM (CFAM L*)", fontsize=18)

axes[1, 1].imshow(lcfam_lightness, cmap="gray")
axes[1, 1].axis("off")
axes[1, 1].set_title("Lightness of LCFAM (LCFAM L*)", fontsize=18)

axes[2, 0].imshow(fam_norm - cfam_lightness, cmap="RdBu_r")
axes[2, 0].axis("off")
axes[2, 0].set_title("Difference Between CFAM L* and FAM", fontsize=18)

axes[2, 1].imshow(fam_norm, cmap="gray")
axes[2, 1].axis("off")
axes[2, 1].set_title("Plain FA Map (FAM)", fontsize=18)

fig.savefig("figure.pdf")