In [1]:

    

%matplotlib inline


    

In [2]:

    

import os
os.chdir('/Users/albert/ndreg')


    

In [3]:

    

from ndreg import *
import matplotlib
import ndio.remote.neurodata as neurodata
import nibabel as nb


    

In [23]:

    

inToken = "Control258"

nd = neurodata()
print(nd.get_metadata(inToken)['dataset']['voxelres'].keys())


    

    




[u'1', u'0', u'3', u'2', u'5', u'4']

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inImg = imgDownload(inToken, resolution=5)
imgShow(inImg, vmax=500)


    

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print(inImg.GetSpacing())


    

    




(3.2e-05, 3.2e-05, 9.999999999999999e-06)

In [26]:

    

refToken = "ara_ccf2"
refImg = imgDownload(refToken)


    

In [27]:

    

imgShow(refImg)


    

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imgShow(refImg, vmax=500)


    

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refAnnoImg = imgDownload(refToken, channel="annotation")
imgShow(refAnnoImg, vmax=1000)


    

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randValues = np.random.rand(1000,3)


    

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randValues = np.concatenate(([[0,0,0]],randValues))


    

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randCmap = matplotlib.colors.ListedColormap (randValues)
imgShow(refAnnoImg, vmax=1000, cmap=randCmap)


    

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imgShow(refImg, vmax=500, newFig=False)
imgShow(refAnnoImg, vmax=1000, cmap=randCmap, alpha=0.2, newFig=False)
plt.show()


    

In [34]:

    

print(inImg.GetSpacing())
print(refImg.GetSpacing())


    

    




(3.2e-05, 3.2e-05, 9.999999999999999e-06)
(0.024999999999999998, 0.024999999999999998, 0.024999999999999998)

In [36]:

    

inImg.SetSpacing([0.01872, 0.01872, 0.005])


    

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print(inImg.GetSpacing())
print(refImg.GetSpacing())


    

    




(0.01872, 0.01872, 0.005)
(0.024999999999999998, 0.024999999999999998, 0.024999999999999998)

In [38]:

    

refImg = imgResample(refImg, spacing=inImg.GetSpacing())
imgShow(refImg, vmax=500)


    

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imgShow(inImg, vmax=500)


    

In [40]:

    

refImg = imgReorient(refImg, "RSA", "LAI")
imgShow(refImg, vmax=500)


    

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(values, bins) = np.histogram(sitk.GetArrayFromImage(refImg), bins=100, range=(0,500))
plt.plot(bins[:-1], values)


    

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lowerThreshold = 100
upperThreshold = sitk.GetArrayFromImage(inImg).max()+1

refImg = sitk.Threshold(refImg,lowerThreshold,upperThreshold,lowerThreshold) - lowerThreshold
imgShow(inImg, vmax = 500)


    

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(values, bins) = np.histogram(sitk.GetArrayFromImage(refImg), bins=100, range=(0,500))
plt.plot(bins[:-1], values)


    

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affine = imgAffineComposite(refImg, inImg, iterations=100, useMI=True, verbose=True)


    

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refImg_affine = imgApplyAffine(refImg, affine, size=inImg.GetSize())
imgShow(inImg_affine, vmax=500)


    

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refImg = imgResample(refImg_affine, spacing=inImg.GetSpacing())
(field, invField) = imgMetamorphosisComposite(refImg, inImg, alphaList=[0.05, 0.02, 0.01], useMI=True, iterations=100, verbose=True)
refImg_lddmm = imgApplyField(refImg_affine, field, size=inImg.GetSize())
imgShow(inImg_lddmm, vmax = 500)