Numpy 3D array into VTK data types for volume rendering?

lassoan · June 3, 2020, 3:41pm

Here is a full example of how to create a volume (vtkImageData) from a numpy array. The code supports scalar, vector, and tensor volumes. If you don’t use this from 3D Slicer then you need to change how you set the image spacing (you need to set it using vtkImageData.SetSpacing):

github.com

Slicer/Slicer/blob/master/Base/Python/slicer/util.py#L1365-L1394


vshape = tuple(reversed(narray.shape))
if len(vshape) == 3:
  # Scalar volume
  vcomponents = 1
elif len(vshape) == 4:
  # Vector volume
  vcomponents = vshape[0]
  vshape = vshape[1:4]
else:
  # TODO: add support for tensor volumes
  raise RuntimeError("Unsupported numpy array shape: "+str(narray.shape))

vimage = volumeNode.GetImageData()
if not vimage:
  import vtk
  vimage = vtk.vtkImageData()
  volumeNode.SetAndObserveImageData(vimage)
import vtk.util.numpy_support
vtype = vtk.util.numpy_support.get_vtk_array_type(narray.dtype)

This file has been truncated. show original

Note that you can get static or interactive (you can rotate around with your mouse) 3D volume rendering from numpy arrays directly in your Jupyter notebook by choosing 3D Slicer as kernel.