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landmarks_centre_mass_missing_vals.py
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import numpy as np
import nibabel as nib
import argparse
def main():
parser = argparse.ArgumentParser()
parser.add_argument("--inputnii", dest="inputnii", help="input segmentation from (nii.gz)", default=None, required=True)
parser.add_argument("--movingnii", dest="movingnii", help="second segmentation from (nii.gz)", default=None, required=False)
parser.add_argument("--savetxt", dest="savetxt", help="output landmark file to (txt)", default=None, required=False)
options = parser.parse_args()
d_options = vars(options)
img = nib.load(d_options['inputnii'])
img_data = img.get_data()
#print(f"img1 shape: {img_data.shape}")
x = np.linspace(0, img_data.shape[0]-1, img_data.shape[0])
y = np.linspace(0, img_data.shape[1]-1, img_data.shape[1])
z = np.linspace(0, img_data.shape[2]-1, img_data.shape[2])
yv, xv, zv = np.meshgrid(y,x,z)
unique = np.unique(img_data)
print(f"Unique image data: {unique}")
positions = np.zeros((len(unique)-1,3))
for i in range(1,len(unique)):
label = (img_data==unique[i]).astype('float32')
xc = np.sum(label*xv)/np.sum(label)
yc = np.sum(label*yv)/np.sum(label)
zc = np.sum(label*zv)/np.sum(label)
positions[i-1,0] = xc
positions[i-1,1] = yc
positions[i-1,2] = zc
if(d_options['savetxt'] is None):
print(('label',unique[i],'x',xc,'y',yc,'z',zc))
if(d_options['movingnii'] is not None):
img2 = nib.load(d_options['movingnii'])
img_data2 = img2.get_data()
print(f"img2 shape: {img_data2.shape}")
unique2 = np.unique(img_data2)
print(f"Unique image data 2: {unique2}")
positions2 = np.zeros((len(unique)-1,3))
for i in range(1,len(unique)):
label = (img_data2==unique[i]).astype('float32')
#print(f"label: {np.unique(label)}")
#print(i)
#print(label.shape)
xc = np.sum(label*xv)/np.sum(label)
yc = np.sum(label*yv)/np.sum(label)
zc = np.sum(label*zv)/np.sum(label)
positions2[i-1,0] = xc
positions2[i-1,1] = yc
positions2[i-1,2] = zc
if(d_options['savetxt'] is None):
print(('label2',unique[i],'x',xc,'y',yc,'z',zc))
error = np.mean(np.sqrt(np.sum(np.power(positions-positions2,2),1)))
print(('landmark error (vox)',error))
with open(d_options['savetxt']+"_mri.txt", "w") as text_file:
for i in range(positions.shape[0]):
text_file.write("%f %f %f %d \n" % (positions[i,0],positions[i,1],positions[i,2],i))
with open(d_options['savetxt']+"_us.txt", "w") as text_file:
for i in range(positions2.shape[0]):
text_file.write("%f %f %f %d \n" % (positions2[i,0],positions2[i,1],positions2[i,2],i))
if __name__ == '__main__':
main()