Difference between revisions of "Moffitt 2014"

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First, convert PGM into PNG (PGM is not recognized by Slicer image readers). Python script to do this is below. Save as a .py file, make sure python is installed, run from command line (modify the input and output directories as needed):
 
First, convert PGM into PNG (PGM is not recognized by Slicer image readers). Python script to do this is below. Save as a .py file, make sure python is installed, run from command line (modify the input and output directories as needed):
  
  import Image
+
<pre>
  input = '/Users/fedorov/ImageData/Moffitt/Label_conversion/MOFFITT/P2/lung/'
+
import Image
  output = '/Users/fedorov/ImageData/Moffitt/Label_conversion/MOFFITT/P2/lung-png/'
+
input = '/Users/fedorov/ImageData/Moffitt/Label_conversion/MOFFITT/P2/lung/'
  for fn in range(len(input)):
+
output = '/Users/fedorov/ImageData/Moffitt/Label_conversion/MOFFITT/P2/lung-png/'
    flong = "%06i" % (fn)
+
for fn in range(len(input)):
    print flong
+
  flong = "%06i" % (fn)
    Image.open(input+str(fn)+'.pgm').save(output+flong+'.png')
+
  print flong
 +
  Image.open(input+str(fn)+'.pgm').save(output+flong+'.png')
 +
</pre>
  
 
Once converted to PNG, run the following script to convert the label slices into 3d format:
 
Once converted to PNG, run the following script to convert the label slices into 3d format:

Revision as of 16:59, 22 December 2014

Home < Moffitt 2014

Logistics

SPL personnel: Andrey Fedorov, Ph.D.

Local hosts: Robert Gillies, Ph.D., Olya Grove, Ph.D.

Dates: Dec 16-17, 2014

Working meeting times:

  • Tue 3-4pm
  • Wed 9-10:30am
  • Wed 1-3pm

Notes and references for the meeting

  • DICOM RT conversion
    • Prerequisites: SlicerRT extension, conversion script added in the last week's version of SlicerRT
    • extensions are located on Windows in
 C:\Users\<your_user_name>\AppData\Roaming\NA-MIC
 Slicer.exe --no-splash --no-main-window --python-script <script> <arguments>
    • to see console messages (in python interactor), run without --no-main-window flag
    • make sure script name has '/', not '\', as path separator
    • make sure image volume for the RTSTRUCT is in the input folder
  • Lung and lesion segmentation
    • FastMarching effect in Editor module
    • GrowCut effect in Editor module, FastGrowCut extension

Batch processing needed:

  1. Load DICOM volume and corresponding label
  2. Extract features
  3. save features in txt file

Follow-up items

  • Scripts for converting legacy PGM segmentations into Slicer-compatible format:

First, convert PGM into PNG (PGM is not recognized by Slicer image readers). Python script to do this is below. Save as a .py file, make sure python is installed, run from command line (modify the input and output directories as needed):

import Image
input = '/Users/fedorov/ImageData/Moffitt/Label_conversion/MOFFITT/P2/lung/'
output = '/Users/fedorov/ImageData/Moffitt/Label_conversion/MOFFITT/P2/lung-png/'
for fn in range(len(input)):
  flong = "%06i" % (fn)
  print flong
  Image.open(input+str(fn)+'.pgm').save(output+flong+'.png')

Once converted to PNG, run the following script to convert the label slices into 3d format:

import sys, os, slicer, vtk

'''
 Usage:
  Slicer.exe --no-splash --no-main-window --python-script converter.py <directory with DICOM files> <directory with segmentation files> <output directory>

'''

dcmDir = sys.argv[1]
segDir = sys.argv[2]
outputDir = sys.argv[3]

print(dcmDir)
print(segDir)
print(outputDir)

# get lists of DICOM and seg files with full path names
# DICOM files fill be sorted by the slice positions for volume reconstruction
dcmList = []
for dcm in os.listdir(dcmDir):
  if len(dcm)-dcm.rfind('.dcm') == 4:
    dcmList.append(dcmDir+'/'+dcm)

# segmentation files need to be sorted,
# assuming here that alphabetical sorting is consistent with the sorting
# applied to DICOM files
segList = []
for seg in os.listdir(segDir):
  # assume segmentations are saved in PNG format, change here if another one
  segList.append(segDir+'/'+seg)
segList.sort()
segList.reverse()

print(str(segList))

scalarVolumePlugin = slicer.modules.dicomPlugins['DICOMScalarVolumePlugin']()

# index input DICOM series
indexer = ctk.ctkDICOMIndexer()
indexer.addDirectory(slicer.dicomDatabase, dcmDir)
indexer.waitForImportFinished()

loadables = scalarVolumePlugin.examine([dcmList])

if len(loadables) == 0:
  print 'Could not parse the DICOM Study!'
  exit()

# load input DICOM volume
dcmVolume = scalarVolumePlugin.load(loadables[0])

# save DICOM volume as single file nrrd format
dcmStorage = slicer.vtkMRMLVolumeArchetypeStorageNode()
dcmStorage.SetWriteFileFormat('nrrd')
dcmStorage.SetFileName(os.path.join(outputDir,'dcm_volume.nrrd'))
dcmStorage.WriteData(dcmVolume)

print('Before instantiating')
segStorage = slicer.vtkMRMLVolumeArchetypeStorageNode()
segStorage.ResetFileNameList()
for seg in segList:
  segStorage.AddFileName(seg)
segStorage.SetFileName(segList[0])
print(str(segList))
segStorage.SetSingleFile(0)
segVolume = slicer.vtkMRMLScalarVolumeNode()
print('Before reading')
segStorage.ReadData(segVolume)
print('After reading')

# convert to unsigned short pixel type
cast = vtk.vtkImageCast()
if vtk.vtkVersion().GetVTKMajorVersion() < 6:
  cast.SetInput(segVolume.GetImageData())
else:
  cast.SetInputData(segVolume.GetImageData())
cast.SetOutputScalarTypeToShort()
cast.Update()

# assign segmentation the same geometry as the DICOM volume
ijkToRAS = vtk.vtkMatrix4x4()
dcmVolume.GetIJKToRASMatrix(ijkToRAS)

segVolume.SetIJKToRASMatrix(ijkToRAS)
segVolume.SetAndObserveImageData(cast.GetOutput())

# save segmentation as a 3d volume in nrrd format
segStorage.SetWriteFileFormat('nrrd')
segStorage.SetFileName(os.path.join(outputDir,'seg_volume.nrrd'))
segStorage.WriteData(segVolume)

sys.exit()

Raul San Jose: Airway inspector development in Slicer: http://lmi.bwh.harvard.edu/~rjosest/