self.connect(itk.LabelImageToLabelMapFilter[ImageType, LabelMapType].New()) # now we can parse the inputs itk.set_inputs(self, args, kargs) ClosestDilateLabelMapFilter = itk.templated_class(ClosestDilateLabelMapFilter) ClosestDilateLabelMapFilter.add_image_templates(itk.INTS, itk.REALS) #nucleiFileName = "gml16_dapi_1_nuclei.nrrd" #inputFileName = "gml16_cenp-fitc_dapi_1.zvi" nucleiFileName = sys.argv[1] inputFileName = "gml16_cenp-fitc_dapi_%s.zvi" % nucleiFileName[11:-12] # read the images cenp = itk.bioformats(inputFileName, ImageType=itk.Image.US3) nuclei = itk.ImageFileReader.IUC3.New(FileName=nucleiFileName) # remove the background before masking the image, in case large background outside the nuclei leak inside the nuclei cenpmedian = itk.MedianImageFilter.IUS3IUS3.New(cenp, Radius=[1, 1, 0]) # add a gaussian filter after the median? sopening = itk.PhysicalSizeOpeningImageFilter.IUS3IUS3.New(cenpmedian, Lambda=0.2) sub = itk.SubtractImageFilter.IUS3IUS3IUS3.New(cenpmedian, sopening) # and dilate the nuclei to be sure to not truncate the spots dilate = ClosestLabelDilateImageFilter.IUC3IF3.New(nuclei, Kernel=itk.strel(3,[3,3,0])) # translate the masks to label objects li2lm = itk.LabelImageToStatisticsLabelMapFilter.IUC3IUS3LM3.New(dilate, sub) lmNuclei = li2lm lmNuclei()
#!/usr/bin/env python # -*- coding: utf-8 -*- import itk, sys, traceback from ExtraData import ExtraData itk.auto_not_in_place() nucleusReader = itk.ImageFileReader.IUC3.New() centromeresReader = itk.ImageFileReader.IUC3.New() centromeresIntReader = itk.bioformats() nucleusLM = itk.LabelImageToShapeLabelMapFilter.IUC3LM3.New(nucleusReader) singleNucleusLM = itk.LabelSelectionLabelMapFilter.LM3.New(nucleusLM, InPlace=False) binaryNucleus = itk.LabelMapToBinaryImageFilter.LM3IUC3.New(singleNucleusLM, ForegroundValue=0, BackgroundValue=255) maurerSingleNucleus = itk.SignedMaurerDistanceMapImageFilter.IUC3IF3.New(binaryNucleus, UseImageSpacing=True, SquaredDistance=False) evfSingleNucleus = itk.ErodedVolumeFractionMapImageFilter.IF3IF3.New(maurerSingleNucleus) maskedCentromeres = itk.LabelMapMaskImageFilter.LM3IUC3.New(nucleusLM, centromeresReader) centromeresLM = itk.LabelImageToStatisticsLabelMapFilter.IUC3IUC3LM3.New(maskedCentromeres, centromeresIntReader) def interpolate(image, pos): li = itk.LinearInterpolateImageFunction.IF3D.New(image) return li.Evaluate( pos ) extra = ExtraData(sys.argv[1], sys.argv[2:], {"nucleus-ext": "-nuclei.nrrd", "spots-ext": "-CENP.nrrd", "spots-are-labeled": "true", "rawspots-ext": "", "rawspots-channel": "0"})