You can try ipyvolume https://github.com/maartenbreddels/ipyvolume for interactive plotting, I found it quite useful.
Also, you can plot them with matplotlib by using marching cubes to obtain the surface mesh but it is quite slow though:
from mpl_toolkits.mplot3d.art3d import Poly3DCollection
import numpy as np
from skimage import measure
def plot_3d(image, threshold=-300):
p = image.transpose(2,1,0)
verts, faces, normals, values = measure.marching_cubes_lewiner(p, threshold)
fig = plt.figure(figsize=(10, 10))
ax = fig.add_subplot(111, projection='3d')
mesh = Poly3DCollection(verts[faces], alpha=0.1)
face_color = [0.5, 0.5, 1]
mesh.set_facecolor(face_color)
ax.add_collection3d(mesh)
ax.set_xlim(0, p.shape[0])
ax.set_ylim(0, p.shape[1])
ax.set_zlim(0, p.shape[2])
plt.show()
The threshold of -300 HU is fine for visualizing chest CT scans but change it if you going to use MRI (check your intensity values distribution) or binary volumes (threshold =0).
There is some example of visualization:
vtkplotter
looked promising, but worked on it for a half an hour and couldn't get it to not crash on.load
withProcess finished with exit code 139 (interrupted by signal 11: SIGSEGV)
– Huberman