三维TIFF图像的读取

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1. 使用Scikit-image

from skimage import io
import numpy as np

io.use_plugin('pil')
ic = io.imread_collection('tow_binary_216_302.tif')
# >>> 

image_3d = io.concatenate_images(ic) # numpy.ndarray
image_3d = image_3d[0]   # binary - 0 vs 255

# Counts the number of non-zero values in the array a.
count = np.count_nonzero(image_3d) # Corresponding to iSlice 216 - 302
# 
coor_x = coor[2]
coor_y = coor[0]
coor_z = coor[1]

# Thresholding and save as images
mask = (image_3d<75)

image_3d[mask]= 0
for i in np.arange(704):
    name='0000'+str(i)
    name = './longibg/blackbgLong'+name[-4:]+'.tif'
    io.imsave(name, image_3d[i,:,:])

使用PyVista

import numpy as np
import pyvista as pv

res = 0.022 # mm
mesh = pv.read('tow_binary_216_302.tif')
mesh = mesh.cast_to_unstructured_grid()
pts = mesh.points

nx, ny, nz = pts.astype(int)[-1,:] + 1
grey_level = mesh['Tiff Scalars'].reshape([nz, ny,nx])

# Return the indices of the elements that are non-zero.  
coor = np.nonzero(grey_level) 
coor_x = coor[2] * res
coor_y = (coor[0] + 215) * res
coor_z = (257-coor[1]) * res

# non-zero point coordinate
coordinate = np.vstack((coor_x, coor_y, coor_z)).T