CODEWITHSUNDEEP
pythonmatplotlibitkmedical
pseudomonas
pseudomonas

Reputation: 432

Blank image appearing

I am using simpleITK to process MRI images in .mha format. I subsequently convert it into a numpy array. I am able to visualize the images using matplotlib.However, if I perform any prerprocessing or I multiply the image by its binary mask, all I get is a blank image. Is there something I am missing. My simplified code is shown below.

import SimpleITK as sitk
import numpy as np
from matplotlib import pyplot as plt
input_image = sitk.ReadImage('MRI.mha')
input_array = sitk.GetArrayFromImage(input_image)
plt.imshow(input_array[0,:,:],cmap = 'gray') # I get an image for this. No preprocessing has been performed.
plt.show()
# However, if I replace input_array after preprocessing, I get a black square.

I think this has something to do with the range of the data, but I am not able to pinpoint where. The image visualized before preprocessing has a maximum value of 744. After preprocessing, this drops down to 4, and that is when problems crop up. Any pointers to where I might be going wrong?

Upvotes: 1

Views: 1137

Answers (1)

mehrtash
mehrtash

Reputation: 930

You should check your image pixel type before any processing. The MRI image volume which you are testing on has a sitkInt32 (Signed 32 bit integer) pixel type. So there is a high chance that your processing (e.g. your division operations) would make your pixel values zeros and you get black images. You can either cast your image to float using SimpleITK:

input_image = sitk.ReadImage('MRI.mha')
print(input_image.GetPixelIDTypeAsString())
input_image = sitk.Cast(input_image,sitk.sitkFloat32)
input_array = sitk.GetArrayFromImage(input_image)

or change your numpy array data type before processing:

input_image = sitk.ReadImage('MRI.mha')
input_array = sitk.GetArrayFromImage(input_image)
input_array = input_array.astype(np.float32)

Read more about pixel types at SimpleITK Image Basics notebook.

Upvotes: 1

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