1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
|
# -----------------------------------------------------------------------
# Copyright: 2010-2021, imec Vision Lab, University of Antwerp
# 2013-2021, CWI, Amsterdam
#
# Contact: astra@astra-toolbox.com
# Website: http://www.astra-toolbox.com/
#
# This file is part of the ASTRA Toolbox.
#
#
# The ASTRA Toolbox is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# The ASTRA Toolbox is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with the ASTRA Toolbox. If not, see <http://www.gnu.org/licenses/>.
#
# -----------------------------------------------------------------------
import astra
import numpy as np
vol_geom = astra.create_vol_geom(256, 256)
proj_geom = astra.create_proj_geom('parallel', 1.0, 384, np.linspace(0,np.pi,180,False))
# For CPU-based algorithms, a "projector" object specifies the projection
# model used. In this case, we use the "line" model.
proj_id = astra.create_projector('line', proj_geom, vol_geom)
# Generate the projection matrix for this projection model.
# This creates a matrix W where entry w_{i,j} corresponds to the
# contribution of volume element j to detector element i.
matrix_id = astra.projector.matrix(proj_id)
# Get the projection matrix as a Scipy sparse matrix.
W = astra.matrix.get(matrix_id)
# Manually use this projection matrix to do a projection:
import scipy.io
P = scipy.io.loadmat('phantom.mat')['phantom256']
s = W.dot(P.ravel())
s = np.reshape(s, (len(proj_geom['ProjectionAngles']),proj_geom['DetectorCount']))
import pylab
pylab.gray()
pylab.figure(1)
pylab.imshow(s)
pylab.show()
# Each row of the projection matrix corresponds to a detector element.
# Detector t for angle p is for row 1 + t + p*proj_geom.DetectorCount.
# Each column corresponds to a volume pixel.
# Pixel (x,y) corresponds to column 1 + x + y*vol_geom.GridColCount.
astra.projector.delete(proj_id)
astra.matrix.delete(matrix_id)
|
