Normalizing image brightness implemented#25
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dvnie1 wants to merge 2 commits intoalexlaurence:masterfrom
Open
Normalizing image brightness implemented#25dvnie1 wants to merge 2 commits intoalexlaurence:masterfrom
dvnie1 wants to merge 2 commits intoalexlaurence:masterfrom
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…ay = nibabel.load(inputfile).get_fdata() [get_data() -> get_fdata()], because prev version caused an error, with the changes it works
…l output images is the same, resulting in a heterogeneous image sequence
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Hi! I was checking your code, and there's something interesting I don't understand. Why do you normalize images using numpy.vectorize()? Why not call normalize function directly? What does np.vectorize do? Thanks! |
Author
Hi, it is basically an inline loop. It is needed, because my normalize() function only normalises one image at a time the way I implemented it. Feel free to change it, there are surely cleaner ways of implementing this :) |
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I fixed a bug, that was caused by using
nibabel.load(inputfile).get_data(). Insteadnibabel.load(inputfile).get_fdata()should be used (get_fdata()instead ofget_data()).Besides that, I implemented the normalization of the input image brightness. This way, all output images have the same brightness and contrast, resulting in a heterogeneous image sequence. The issue was caused by the fact, that NIFTI images have brightness values from -3000 to 3000, but PNGs only from 0 to 255. This was solved with a basic linear transformation.