# Original image python dataformat
originalImageP = np.zeros((1, 128, 128)) # matrix 128 x 128 gevuld met 0'en
for i in range(128):
for j in range(128):
if (i - 40) * (i - 40) + (j - 40) * (j - 40) + 10 < 30:
originalImageP[0, i, j] = 1
#plt.figure(1), plt.title('Original image'), plt.imshow(originalImageP[0,:,:]), plt.show()
# Stir data format instance with the size of the original image in python (not yet filled!)
originalImageS = stir.FloatVoxelsOnCartesianGrid(
projdata_info, 1,
stir.FloatCartesianCoordinate3D(stir.make_FloatCoordinate(0, 0, 0)),
stir.IntCartesianCoordinate3D(
stir.make_IntCoordinate(
np.shape(originalImageP)[0],
np.shape(originalImageP)[1],
np.shape(originalImageP)[2])))
# Filling the stir data format with the original image
fillStirSpace(originalImageS, originalImageP)
# Initialize the projection matrix (using ray-tracing)
# Het motion model doet nu niets, maar is nodig omdat Stir anders flipt
MotionModel = stir.MotionModel()
MotionModel.setOffset(0.0)
projmatrix = stir.ProjMatrixByBinUsingRayTracing(MotionModel)
projmatrix.set_num_tangential_LORs(nLOR)
projmatrix.set_up(projdata_info, originalImageS)
# Create projectors
forwardprojector = stir.ForwardProjectorByBinUsingProjMatrixByBin(projmatrix)
image = np.concatenate((tmpX, image), axis = 1)
image = np.concatenate((image, tmpX), axis = 1)
# Block phantom
'''
image = np.zeros((160,160))
image[65:95, 65:95] = 1
'''
## TEST: Recons maken na verschillende iteraties -> som berekenen
testList = []
sumList = []
test = stir.FloatVoxelsOnCartesianGrid(projdata_info, 1,
stir.FloatCartesianCoordinate3D(stir.make_FloatCoordinate(0,0,0)),
stir.IntCartesianCoordinate3D(stir.make_IntCoordinate(1,200,200))) # Lengte moet je gokken/weten
for i in range(8):
test = test.read_from_file('output_config_Proj_1_{0}.hv'.format(i+1))
testList.append(stirextra.to_numpy(test))
sumList.append(np.sum(stirextra.to_numpy(test)[0,:,:]))
axisX = range(1,9,1)
plt.plot(axisX, sumList, axisX, [np.sum(image)]*len(axisX)), plt.title('Sum of OSMAPOSL recon (blue), sum of original image (green)'), plt.xlabel('Iteration number')
plt.savefig('./Plaatjes/OSMAPOSLSumAfterIterations.png')
plt.show()
for i in range(8):
plt.subplot(2,4,i+1), plt.imshow(testList[i][0,:,:], cmap=plt.cm.Greys_r, interpolation=None, vmin = 0), plt.title('Iteration {0}'.format(i))
plt.savefig('./Plaatjes/OSMAPOSLReconAfterIterations.png'.format(trueShiftPixels))
plt.show()
# Setup projection data
projdata_info = stir.ProjDataInfo.ProjDataInfoCTI(scanner, span, max_ring_diff, scanner.get_max_num_views(), scanner.get_max_num_non_arccorrected_bins(), False)
# Phantoms for each time frame
phantomP = []
# Create the individual time frames, the phantom is shifted in each frame w.r.t. the previous one
for iFrame in range(nFrames):
tmp = np.zeros((1, 128, 128))
tmp[0, (10+iFrame*trueShiftPixels):(30+iFrame*trueShiftPixels), 60:80] = 1
phantomP.append(tmp)
originalImageP = phantomP[0]
originalImageS = stir.FloatVoxelsOnCartesianGrid(projdata_info, 1,
stir.FloatCartesianCoordinate3D(stir.make_FloatCoordinate(0,0,0)),
stir.IntCartesianCoordinate3D(stir.make_IntCoordinate(np.shape(originalImageP)[0],np.shape(originalImageP)[1],np.shape(originalImageP)[2] )))
fillStirSpace(originalImageS, originalImageP)
plt.figure(1)
plt.subplot(1,2,1), plt.title('Phantom TF 1'), plt.imshow(phantomP[0][0,:,:])
plt.subplot(1,2,2), plt.title('Phantom TF 2'), plt.imshow(phantomP[1][0,:,:])
plt.show()
phantomS = []
for iFrame in range(nFrames):
imageS = stir.FloatVoxelsOnCartesianGrid(projdata_info, 1,
stir.FloatCartesianCoordinate3D(stir.make_FloatCoordinate(0,0,0)),
stir.IntCartesianCoordinate3D(stir.make_IntCoordinate(np.shape(originalImageP)[0],np.shape(originalImageP)[1],np.shape(originalImageP)[2] )))
fillStirSpace(imageS, phantomP[iFrame])
phantomS.append(imageS)
nLOR = 10
scanner = stir.Scanner(stir.Scanner.Siemens_mMR)
scanner.set_num_rings(nRings)
projdata_info = stir.ProjDataInfo.ProjDataInfoCTI(
scanner, span, max_ring_diff, scanner.get_max_num_views(),
scanner.get_max_num_non_arccorrected_bins(), False)
image = np.zeros((1, 160, 160))
image[0, 65:95, 65:95] = 1
originalImageS = stir.FloatVoxelsOnCartesianGrid(
projdata_info, 1,
stir.FloatCartesianCoordinate3D(stir.make_FloatCoordinate(0, 0, 0)),
stir.IntCartesianCoordinate3D(stir.make_IntCoordinate(1, 160, 160)))
fillStirSpace(originalImageS, image)
guessP = np.ones((1, 160, 160)) # Voor het blokje
guessS = stir.FloatVoxelsOnCartesianGrid(
projdata_info, 1,
stir.FloatCartesianCoordinate3D(stir.make_FloatCoordinate(0, 0, 0)),
stir.IntCartesianCoordinate3D(stir.make_IntCoordinate(1, 160, 160)))
fillStirSpace(guessS, guessP)
slope = 0.0
offSet = 0.0
nFrames = 1
MotionModel = stir.MotionModel(nFrames, slope,
scanner.set_num_rings(nRings)
span = 1
max_ring_diff = 0
#Setup projection data
projdata_info = stir.ProjDataInfo.ProjDataInfoCTI(
scanner, span, max_ring_diff, scanner.get_max_num_views(),
scanner.get_max_num_non_arccorrected_bins(), False)
#Setup Recon space
phantomspace = stir.FloatVoxelsOnCartesianGrid(
projdata_info, 1,
stir.FloatCartesianCoordinate3D(stir.make_FloatCoordinate(0, 0, 0)),
stir.IntCartesianCoordinate3D(
stir.make_IntCoordinate(
np.shape(p)[0],
np.shape(p)[1],
np.shape(p)[2])))
reconspace = stir.FloatVoxelsOnCartesianGrid(
projdata_info, 1,
stir.FloatCartesianCoordinate3D(stir.make_FloatCoordinate(0, 0, 0)),
stir.IntCartesianCoordinate3D(
stir.make_IntCoordinate(
np.shape(p)[0],
np.shape(p)[1],
np.shape(p)[2])))
imspaceError = stir.FloatVoxelsOnCartesianGrid(
projdata_info, 1,
stir.FloatCartesianCoordinate3D(stir.make_FloatCoordinate(0, 0, 0)),
stir.IntCartesianCoordinate3D(
#ready up the stir
scanner = stir.Scanner(stir.Scanner.E1104)
scanner.set_num_rings(55)
#Setup projection data
span = 11
#projdata_info = stir.ProjDataInfo.ProjDataInfoCTI(scanner, span, max_ring_diff, 168, scanner.get_max_num_non_arccorrected_bins(), False)
projdata_info2D = stir.ProjDataInfo.ProjDataInfoCTI(scanner, span, max_ring_diff, 168, scanner.get_max_num_non_arccorrected_bins(), False)
guessVolume = stir.FloatVoxelsOnCartesianGrid(projdata_info2D, 1,
stir.FloatCartesianCoordinate3D(stir.make_FloatCoordinate(0,0,0)),
stir.IntCartesianCoordinate3D(stir.make_IntCoordinate(sizeOfVolumeInVoxels[0], sizeOfVolumeInVoxels[1], sizeOfVolumeInVoxels[2])))
guessVolume.fill(1)
ErrorVolume = stir.FloatVoxelsOnCartesianGrid(projdata_info2D, 1,
stir.FloatCartesianCoordinate3D(stir.make_FloatCoordinate(0,0,0)),
stir.IntCartesianCoordinate3D(stir.make_IntCoordinate(sizeOfVolumeInVoxels[0], sizeOfVolumeInVoxels[1], sizeOfVolumeInVoxels[2])))
ErrorVolume.fill(0)
forwardSino2D = stir.ProjDataInMemory(stir.ExamInfo(), projdata_info2D)
forwardSino2D.fill(0)
#Initialize the projection matrix (using ray-tracing)
projmatrix2D = stir.ProjMatrixByBinUsingRayTracing()
nLOR = 10
projmatrix2D.set_num_tangential_LORs(nLOR)
projmatrix2D.set_up(projdata_info2D, guessVolume)