Exemplo n.º 1
0
def ThresholdMaxEntropy(imp0):
    """Thresholds image and returns thresholded image, merge code still quite clumsy but functional"""
    imp0 = IJ.getImage()
    impthres = imp0.duplicate()
    imp01 = ImagePlus("Channel1", ChannelSplitter.getChannel(imp0, 1))
    imp02 = ImagePlus("Channel2", ChannelSplitter.getChannel(imp0, 2))
    imp001 = imp01.duplicate()
    imp002 = imp02.duplicate()
    IJ.setAutoThreshold(imp001, "MaxEntropy dark")
    IJ.run(imp001, "Convert to Mask", "")
    IJ.run(imp001, "Divide...", "value=255")
    IJ.setAutoThreshold(imp002, "MaxEntropy dark")
    IJ.run(imp002, "Convert to Mask", "")
    IJ.run(imp002, "Divide...", "value=255")
    ic = ImageCalculator()
    imp0001 = ic.run("Multiply create", imp01, imp001)
    ic2 = ImageCalculator()
    imp0002 = ic2.run("Multiply create", imp02, imp002)
    imp0001.copy()
    impthres.setC(1)
    impthres.paste()
    imp0002.copy()
    impthres.setC(2)
    impthres.paste()
    imp01.close()
    imp02.close()
    imp001.close()
    imp002.close()
    imp0001.close()
    imp0002.close()
    return impthres
Exemplo n.º 2
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	def getCroppedChannels(self, imp, cell):
		splitter = ChannelSplitter()
		imp.setRoi(None)
		if cell.mode3D:
			cropRoi = cell.getCropRoi()
		else:
			cropRoi = cell.roi
		if cropRoi is None:
			return None
		crop = cropRoi.getBounds()
		channels = []
		for c in range(1, imp.getNChannels() + 1):
			slices = ImageStack(crop.width, crop.height)
			channel = splitter.getChannel(imp, c)
			for z in range(1, channel.getSize() + 1):
				zslice = channel.getProcessor(z)
				zslice.setRoi(cropRoi)
				nslice = zslice.crop()
				if cell.mode3D:
					oroi = cell.slices[z - 1].roi	
				else:
					oroi = cell.roi
				if oroi is not None:
					roi = oroi.clone()
					bounds = roi.getBounds()
					roi.setLocation(bounds.x - crop.x, bounds.y - crop.y)
					nslice.setColor(Color.black)
					nslice.fillOutside(roi)
					slices.addSlice(nslice)
			channels.append(ImagePlus("Channel %i" % c, slices))
		return channels
Exemplo n.º 3
0
def split_channels_blue(imp):
    #Create blue channel
    original_blue = ChannelSplitter.getChannel(imp, 3)
    original_blue_IP = ImagePlus(filename, original_blue)
    fs = FileSaver(original_blue_IP)
    folder = "/Users/gceleste/Desktop/test/channels"
    filepath = folder + "/" + "{}_bluechannel.tif".format(filename)
    fs.saveAsTiff(filepath)
    #Open blue channel image.
    blue = IJ.open(filepath)
    #blue_IP = ImagePlus(filename, blue)
    IJ.run(
        "3D Objects Counter",
        "threshold=100 slice=1 min.=50 max.=1447680 exclude_objects_on_edges objects summary"
    )
    #Save blue object map
    blue_map = IJ.getImage()
    fs = FileSaver(blue_map)
    folder = "/Users/gceleste/Desktop/test/object maps"
    filepath = folder + "/" + "{}_objectmap(blue).jpg".format(filename)
    fs.saveAsJpeg(filepath)
    #Close blue channel image.
    blue_map.close()
    blue = IJ.getImage()
    blue.close()
Exemplo n.º 4
0
def split_channels_red(imp):
    #Create red channel
    original_red = ChannelSplitter.getChannel(imp, 1)
    original_red_IP = ImagePlus(filename, original_red)
    fs = FileSaver(original_red_IP)
    folder = "/Users/gceleste/Desktop/test/channels"
    filepath = folder + "/" + "{}_redchannel.tif".format(filename)
    fs.saveAsTiff(filepath)
    #Open red channel image.
    red = IJ.open(filepath)
    #red_IP = ImagePlus(filename, red)
    IJ.run(
        "3D Objects Counter",
        "threshold=130 slice=1 min.=50 max.=1447680 exclude_objects_on_edges objects summary"
    )
    #Save red object map.
    red_map = IJ.getImage()
    fs = FileSaver(red_map)
    folder = "/Users/gceleste/Desktop/test/object maps"
    filepath = folder + "/" + "{}_objectmap(red).jpg".format(filename)
    fs.saveAsJpeg(filepath)
    #Close red channel images.
    red_map.close()
    red = IJ.getImage()
    red.close()
Exemplo n.º 5
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	def previewImage(self, imp):
		roi = imp.getRoi()
		splitter = ChannelSplitter()
		channels = []
		for c in range(1, imp.getNChannels() + 1):
			channel = ImagePlus("Channel %i" % c, splitter.getChannel(imp, c))
			projector = ZProjector(channel)
			projector.setMethod(ZProjector.MAX_METHOD)
			projector.doProjection()
			channels.append(projector.getProjection())
		image = RGBStackMerge.mergeChannels(channels, False)
		image.title = imp.title + " MAX Intensity"
		image.luts = imp.luts
		imp.setRoi(roi)
		return image
Exemplo n.º 6
0
def getPreview(image):
	enhancer = ContrastEnhancer()
	projector = ZProjector()
	splitter = ChannelSplitter()
	imp1 = ImagePlus("CH1", )
	width, height, channels, slices, frames = image.getDimensions()
	chimps = []
	for ch in range(1, channels + 1):
		projector = ZProjector(ImagePlus("C%i" % ch, splitter.getChannel(image, ch)))
		projector.setMethod(ZProjector.MAX_METHOD)
		projector.doProjection()
		proj = projector.getProjection()
		enhancer.equalize(proj)
		chimps.append(proj)
		
	return RGBStackMerge.mergeChannels(chimps, False)
Exemplo n.º 7
0
    f for f in os.listdir(os.path.join(inputPath)) if f.lower()[0].isalnum()
]

for sample in imagelist:
    rmi.reset()
    IJ.run('Close All')
    sample_label = sample.split('.')[0]
    outputFile = os.path.join(outputPath, sample_label + '.zip')
    if not os.path.exists(outputFile):  #Check that file does not yet exists
        print 'Segmenting ' + sample_label

        #Load images
        imp = IJ.openImage(os.path.join(inputPath, sample))

        #Split channels
        nucleistack = cs.getChannel(imp, 1)
        cellstack = cs.getChannel(imp, 2)

        #Select relevant slices by average intensity of cell marker
        avgI = []
        for sliceIndex in range(1, cellstack.size() + 1):  #loop over slices
            ip = cellstack.getProcessor(sliceIndex)
            avgI.append(ip.getStats().mean)  #get average intensity
        avgth1 = percentile(sorted(avgI), parameters['avgI_low'])
        avgth2 = percentile(sorted(avgI), parameters['avgI_high'])
        sel = [
            avgI.index(i) + 1 for i in avgI if (i >= avgth1 and i <= avgth2)
        ]  #pick slices with intermediate average intensity
        print sel
        #Get ROIs
        rois = []
Exemplo n.º 8
0
results = ResultsTable()
for imageFile in os.listdir(inputDir):
	print "Opening " + imageFile
	try:
		images = BF.openImagePlus(inputDir + imageFile)
		image = images[0]
	except UnknownFormatException:
		continue
	preview = getPreview(image)
	preview.show()
	rm = RoiManager()
	dialog = WaitForUserDialog("Action required", "Please select regions of interest in this image. Click OK when done.")
	dialog.show()
	rm.close()
	splitter = ChannelSplitter()
	imp1 = ImagePlus("CH1", splitter.getChannel(image, imageA))
	imp2 = ImagePlus("CH2", splitter.getChannel(image, imageB))
	title = image.getTitle()
	title = title[:title.rfind('.')]
	image.close()
	preview.close()
	ch1 = ImagePlusAdapter.wrap(imp1)
	ch2 = ImagePlusAdapter.wrap(imp2)

	for roi in rm.getRoisAsArray():
		container = createContainer(roi, ch1, ch2)
		img1 = container.getSourceImage1()
		img2 = container.getSourceImage2()
		mask = container.getMask()
		
		thr1, thrimp1 = calculateThreshold(imp1, roi, methods[0])
Exemplo n.º 9
0
if pixel_size is None:
  if objective == 20 and microscope == "SD":
    pixel_size = 0.5089
  else:
    pixel_size = 1.0

files = glob.glob(input_dir + "*.tif")
files.sort()

frame_i = 1
for file in files:
  print("Processing frame \033[1m" + str(frame_i) + "\033[0m")
  frame = IJ.openImage(file) # ImagePlus

  # Get just the signal channel
  frame_stack = channel_splitter.getChannel(frame, channel) # ImageStack
  frame = ImagePlus("Channel " + str(channel), frame_stack)

  # Map signal to entire 16-bit range
  contrast_enhancer.stretchHistogram(frame, 0.01)
  processor = frame.getProcessor()
  if(processor.getBitDepth() == 32):
    processor.setMinAndMax(0, 1.0)
  else:
    processor.setMinAndMax(0, processor.maxValue())

  frame = ImagePlus("Frame " + str(frame_i), processor)

  # Convert to 8-bit, grayscale
  converter = ImageConverter(frame)
  converter.convertToGray8()