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Signal Reconstruction Using Spherical Harmonics
This example shows how you can use a spherical harmonics (SH) function to reconstruct any spherical function using DIPY_. In order to generate a signal, we will need to generate an evenly distributed sphere. Let’s import some standard packages.
import numpy as np
from dipy.core.sphere import disperse_charges, Sphere, HemiSphere
We can first create some random points on a HemiSphere using spherical
polar coordinates.
n_pts = 64
theta = np.pi * np.random.rand(n_pts)
phi = 2 * np.pi * np.random.rand(n_pts)
hsph_initial = HemiSphere(theta=theta, phi=phi)
Next, we call disperse_charges which will iteratively move the points so
that the electrostatic potential energy is minimized. In hsph_updated we
have the updated HemiSphere with the points nicely distributed on the
hemisphere.
hsph_updated, potential = disperse_charges(hsph_initial, 5000)
sphere = Sphere(xyz=np.vstack((hsph_updated.vertices, -hsph_updated.vertices)))
We now need to create our initial signal. To do so, we will use our sphere’s
vertices as the sampled points of our spherical function (SF). We will
use multi_tensor_odf to simulate an ODF. For more information on how to use
DIPY_ to simulate a signal and ODF, see example_simulate_multi_tensor.
from dipy.sims.voxel import multi_tensor_odf
mevals = np.array([[0.0015, 0.00015, 0.00015],
[0.0015, 0.00015, 0.00015]])
angles = [(0, 0), (60, 0)]
odf = multi_tensor_odf(sphere.vertices, mevals, angles, [50, 50])
from dipy.viz import window, actor
# Enables/disables interactive visualization
interactive = False
scene = window.Scene()
scene.SetBackground(1, 1, 1)
odf_actor = actor.odf_slicer(odf[None, None, None, :], sphere=sphere)
odf_actor.RotateX(90)
scene.add(odf_actor)
print('Saving illustration as symm_signal.png')
window.record(scene, out_path='symm_signal.png', size=(300, 300))
if interactive:
window.show(scene)
Saving illustration as symm_signal.png
Illustration of the simulated signal sampled on a sphere of 64 points per hemisphere
We can now express this signal as a series of SH coefficients using
sf_to_sh. This function converts a series of SF coefficients in a series of
SH coefficients. For more information on SH basis, see Spherical Harmonic bases. For
this example, we will use the descoteaux07 basis up to a maximum SH order
of 8.
from dipy.reconst.shm import sf_to_sh
# Change this value to try out other bases
sh_basis = 'descoteaux07'
# Change this value to try other maximum orders
sh_order = 8
sh_coeffs = sf_to_sh(odf, sphere, sh_order, sh_basis)
sh_coeffs is an array containing the SH coefficients multiplying the SH
functions of the chosen basis. We can use it as input of sh_to_sf to
reconstruct our original signal. We will now reproject our signal on a high
resolution sphere using sh_to_sf.
from dipy.data import get_sphere
from dipy.reconst.shm import sh_to_sf
high_res_sph = get_sphere('symmetric724').subdivide(2)
reconst = sh_to_sf(sh_coeffs, high_res_sph, sh_order, sh_basis)
scene.clear()
odf_actor = actor.odf_slicer(reconst[None, None, None, :], sphere=high_res_sph)
odf_actor.RotateX(90)
scene.add(odf_actor)
print('Saving output as symm_reconst.png')
window.record(scene, out_path='symm_reconst.png', size=(300, 300))
if interactive:
window.show(scene)
Saving output as symm_reconst.png
Reconstruction of a symmetric signal on a high resolution sphere using a symmetric basis
While a symmetric SH basis works well for reconstructing symmetric SF, it fails to do so on asymmetric signals. We will now create such a signal by using a different ODF for each hemisphere of our sphere.
mevals = np.array([[0.0015, 0.0003, 0.0003]])
angles = [(0, 0)]
odf2 = multi_tensor_odf(sphere.vertices, mevals, angles, [100])
n_pts_hemisphere = int(sphere.vertices.shape[0] / 2)
asym_odf = np.append(odf[:n_pts_hemisphere], odf2[n_pts_hemisphere:])
scene.clear()
odf_actor = actor.odf_slicer(asym_odf[None, None, None, :], sphere=sphere)
odf_actor.RotateX(90)
scene.add(odf_actor)
print('Saving output as asym_signal.png')
window.record(scene, out_path='asym_signal.png', size=(300, 300))
if interactive:
window.show(scene)
Saving output as asym_signal.png
Illustration of an asymmetric signal sampled on a sphere of 64 points per hemisphere
Let’s try to reconstruct this SF using a symmetric SH basis.
sh_coeffs = sf_to_sh(asym_odf, sphere, sh_order, sh_basis)
reconst = sh_to_sf(sh_coeffs, high_res_sph, sh_order, sh_basis)
scene.clear()
odf_actor = actor.odf_slicer(reconst[None, None, None, :], sphere=high_res_sph)
odf_actor.RotateX(90)
scene.add(odf_actor)
print('Saving output as asym_reconst.png')
window.record(scene, out_path='asym_reconst.png', size=(300, 300))
if interactive:
window.show(scene)
Saving output as asym_reconst.png
Reconstruction of an asymmetric signal using a symmetric SH basis
As we can see, a symmetric basis fails to properly represent asymmetric SF.
Fortunately, DIPY_ also implements full SH bases, which can deal with symmetric
as well as asymmetric signals. For this tutorial, we will demonstrate it using
the descoteaux07 full SH basis by setting full_basis=true.
sh_coeffs = sf_to_sh(asym_odf, sphere, sh_order,
sh_basis, full_basis=True)
reconst = sh_to_sf(sh_coeffs, high_res_sph, sh_order,
sh_basis, full_basis=True)
scene.clear()
odf_actor = actor.odf_slicer(reconst[None, None, None, :], sphere=high_res_sph)
odf_actor.RotateX(90)
scene.add(odf_actor)
print('Saving output as asym_reconst_full.png')
window.record(scene, out_path='asym_reconst_full.png', size=(300, 300))
if interactive:
window.show(scene)
Saving output as asym_reconst_full.png
Reconstruction of an asymmetric signal using a full SH basis
As we can see, a full SH basis properly reconstruct asymmetric signal.
Total running time of the script: ( 0 minutes 3.474 seconds)