text: import SimpleITK as sitk
  import os,cv2
  import numpy as np
  from scipy.spatial.distance import cdist
  o_img_nii = '/mnt/data9/cam/pre'
  o_msk_nii = '/mnt/data9/cam/mask'
  o_lung_nii = '/mnt/data9/cam/lung'
  f=open('distance.txt','w')
  f.writelines('name'+','+'value'+'\n')
  for item in os.listdir(o_lung_nii):
      try:
          lung=sitk.ReadImage(os.path.join(o_lung_nii,item))
          lung=sitk.GetArrayFromImage(lung)*255
          #lung=np.stack([lung,lung,lung],0)
          side=cv2.Canny(lung.astype(np.uint8), 200, 300)
          side_points=np.array(np.where(side==255))
          #cv2.imwrite('temp.jpg',canny)
          mask=sitk.ReadImage(os.path.join(o_msk_nii,item))
          mask=sitk.GetArrayFromImage(mask)
          index=np.where(mask>0)
          centroid=np.mean(index,1)
          dist = cdist(centroid[np.newaxis,:], side_points.transpose(), 'euclidean')
          dist=dist.min()
          f.writelines(item+','+str(dist)+'\n')
          print(item,dist)
      except:
          continue
  f.close()
  