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

• Prerequisites: nightly and stable build of Slicer, Windows 64bit http://download.slicer.org

• 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

• • to enable showing hidden folders see http://windows.microsoft.com/en-us/windows/show-hidden-files#show-hidden-files=windows-7
  • running Slicer python script from the command line:

 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

• Interfacing Matlab
  • MatlabBridge extension
  • Tutorial, documentation, teaching videos: http://www.slicer.org/slicerWiki/index.php/Documentation/Nightly/Extensions/MatlabBridge

• General introduction user tutorials: http://wiki.slicer.org/slicerWiki/index.php/Documentation/4.3/Training#General_Introduction
• Developer tutorials: http://wiki.slicer.org/slicerWiki/index.php/Documentation/4.3/Training#Tutorials_for_software_developers
• Feature extraction: HeterogeneityCAD extension: http://wiki.slicer.org/slicerWiki/index.php/Documentation/Nightly/Modules/HeterogeneityCAD

Batch processing needed:

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

Follow-up items

• Lung and nodule segmentation and feature extraction screencast: http://youtu.be/koHKAJWGNhU

• 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/