Hi,
I have a CT volume and its corresponding binary mask image volume of the
liver.
I just want to ray-trace through a binary mask image volume to generate
mask-projection DRRs.
The DRRs can be sucessfully genrated from the CT volume, but when I passed
the binary mask volume, I did not get the correct result.
Could anyone please assist me in resolving this problem ? What kind of
change should I make to generate these DRRs ?
The code, resulted DRR versions for CT and mask, CT volume and the binary
mask volume attached herewith for your further reference.
reference_CT.nii.gz
<https://drive.google.com/file/d/1p6ODn6gK11v2pU1OmRd-8SyXG5nwzZf6/view?usp=drive_web>
reference_liver_binary_mask.nii.gz
<https://drive.google.com/file/d/1I3J3zUtdgT6ge6kY8EspiPjIqhQi8-eh/view?usp=drive_web>
import sys
import itk
from itk import RTK as rtk
import itk
import numpy as np
def generateDRRs(input_file=None, output_file=None, sid=1000., sdd=1536.,
gantryAngle=0.,
projOffsetX=0., projOffsetY=0., outOfPlaneAngle=0.,
inPlaneAngle=0.,
sourceOffsetX=0., sourceOffsetY=0., dx=512, dy=512):
CT = itk.imread(input_file, pixel_type=itk.F)
# The CT volume is not correct orientation compatible to the RTK convention
and point (0,0,0) mm is not in the CT image
# and this is the default centre of rotation in RTK. Therefore change the
origin and the direction to use
# RTK convention to get the correct DRR as expected.
# the input of the Joseph-Filter needs to be oriented in the y-direction.
In RTK, the rotation axis is y.
# changed the direction and the iamge origin of the image volume to have
the volume in the xz-layer in the y-direction.
# Three rotation angles are used to define the orientation of the detector.
# The ZXY convention of Euler angles is used for detector orientation where
GantryAngle is the rotation around y,
# OutOfPlaneAngle the rotation around x and InPlaneAngle the rotation
around z.
# change the direction and origin to align with the RTK convention
CTDirection=np.zeros([3,3])
CTDirection[0,0]=1.
CTDirection[1,2]=1.
CTDirection[2,1]=1.
CT.SetDirection(itk.matrix_from_array(CTDirection))
CT.SetOrigin([CT.GetOrigin()[0],CT.GetOrigin()[2],-CT.GetOrigin()[1]])
CTarray = itk.array_view_from_image(CT)
# add 1000 to CT numbers to put air at 0
CTarray += 1000
# Defines the image type
Dimension_CT = 3
PixelType = itk.F
ImageType = itk.Image[PixelType, Dimension_CT]
# Create a stack of empty projection images
ConstantImageSourceType = rtk.ConstantImageSource[ImageType]
constantImageSource = ConstantImageSourceType.New()
# Set origin and spacing based on the Elekta configuration
constantImageSource.SetOrigin([-204.4,-204.4,0])
constantImageSource.SetSpacing([0.8,0.8,0.8])
constantImageSource.SetSize([dx, dy, 1])
constantImageSource.SetConstant(0.)
# Defines the RTK geometry object
geometry = rtk.ThreeDCircularProjectionGeometry.New()
geometry.AddProjection(sid, sdd, gantryAngle, -projOffsetX, -projOffsetY,
outOfPlaneAngle, inPlaneAngle, sourceOffsetX, sourceOffsetY)
REIType = rtk.JosephForwardProjectionImageFilter[ImageType, ImageType]
rei = REIType.New()
rei.SetGeometry(geometry)
rei.SetInput(0, constantImageSource.GetOutput())
rei.SetInput(1, CT)
rei.Update()
Dimension = 3
OutputPixelType = itk.UC
OutputImageType = itk.Image[OutputPixelType, Dimension]
RescaleType = itk.RescaleIntensityImageFilter[ImageType, OutputImageType]
rescaler = RescaleType.New()
rescaler.SetOutputMinimum(0)
rescaler.SetOutputMaximum(255)
rescaler.SetInput(rei.GetOutput())
rescaler.Update()
# Out of some reason, the computed projection is upsided-down.
# Here we use a FilpImageFilter to flip the images in y direction.
FlipFilterType = itk.FlipImageFilter[OutputImageType]
flipFilter = FlipFilterType.New()
FlipAxesArray = itk.FixedArray[itk.D, 3]()
FlipAxesArray[0] = 0
FlipAxesArray[1] = 1
FlipAxesArray[2] = 0
flipFilter.SetFlipAxes(FlipAxesArray)
flipFilter.SetInput(rescaler.GetOutput())
flipFilter.Update()
WriteType = itk.ImageFileWriter[OutputImageType]
writer = WriteType.New()
writer.SetFileName(output_file)
writer.SetInput(flipFilter.GetOutput())
writer.Update()
ct_file = './reference_CT.nii.gz'
binary_mask_file = './reference_liver_binary_mask.nii.gz'
out_ct_drr_file = './ct_drr_324.png'
out_mask_drr_file = './mask_drr_324.png'
offset_X = 117.085998535
offset_Y = 3.948999882
# generate DRRs fro CT volume
generateDRRs(input_file=ct_file, output_file=out_ct_drr_file,
projOffsetX=offset_X, projOffsetY=offset_Y, gantryAngle=324)
# generate DRRs from binary mask volume
generateDRRs(input_file=binary_mask_file, output_file=out_mask_drr_file,
projOffsetX=offset_X, projOffsetY=offset_Y, gantryAngle=324)_______________________________________________
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