#imagefile = r"/datadisk1/tuxedo/Github/Tools_and_Scripts/Fiji/scripts/3d_nuclei_image_holes.ome.tiff" imagefile = r"/datadisk1/tuxedo/Github/Tools_and_Scripts/Fiji/scripts/Osteosarcoma_01.ome.tiff" imagefile = r'"C:\Temp\input\Osteosarcoma_01.ome.tiff" corrf = 1.0 if stackopt: thcmd = method + ' ' + background_threshold + ' stack' if not stackopt: thcmd = method + ' ' + background_threshold # open image stack imp, MetaInfo = ImportTools.openfile(imagefile) imp = MiscTools.splitchannel(imp, 3) imp = ThresholdTools.apply_threshold(imp, method=method, background_threshold='dark', stackopt=stackopt, corrf=corrf) imp.show()
doPresmooth=dopresmooth,
correctCorners=correct_corners)
# filter image
if filtertype != 'NONE':
log.info('Apply Filter : ' + filtertype)
imp = FilterTools.apply_filter(imp,
radius=filter_radius,
filtertype=filtertype)
# apply threshold
log.info('Apply Threshold ...')
imp = ThresholdTools.apply_threshold(imp,
method=threshold_method,
background_threshold=threshold_background,
stackopt=threshold_stackoption,
corrf=threshold_corr)
if watershed:
imp = WaterShedTools.run_watershed(imp,
mj_normalize=True,
mj_dynamic=1,
mj_connectivity=watershed_connectivity)
pastack, results = AnalyzeTools.analyzeParticles(imp,
minsize,
maxsize,
mincirc,
maxcirc,
filename=imagefile,
def run(imagefile):
# Opening the image
log.log(LogLevel.INFO, 'Opening Image: ' + imagefile)
# open image file and get a specific series
imp, MetaInfo = ImportTools.openfile(imagefile)
log.log(LogLevel.INFO, 'File Extension : ' + MetaInfo['Extension'])
if 'ResolutionCount' in MetaInfo:
log.log(LogLevel.INFO,
'Resolution Count : ' + str(MetaInfo['ResolutionCount']))
if 'SeriesCount' in MetaInfo:
log.log(LogLevel.INFO,
'SeriesCount : ' + str(MetaInfo['SeriesCount']))
if 'SizeC' in MetaInfo:
log.log(LogLevel.INFO, 'Channel Count : ' + str(MetaInfo['SizeC']))
# do the processing
log.log(LogLevel.INFO, 'Start Processing ...')
if EXTRACT_CHANNEL:
# get the correct channel
if MetaInfo['SizeC'] > 1:
log.log(LogLevel.INFO, 'Extract Channel : ' + str(CHINDEX))
imps = ChannelSplitter.split(imp)
imp = imps[CHINDEX - 1]
# correct background using rolling ball
if CORRECT_BACKGROUND:
log.log(LogLevel.INFO, 'Rolling Ball Background subtraction...')
imp = FilterTools.apply_rollingball(imp,
radius=RB_RADIUS,
createBackground=CREATEBACKGROUND,
lightBackground=LIGHTBACKGROUND,
useParaboloid=USEPARABOLOID,
doPresmooth=DOPRESMOOTH,
correctCorners=CORRECTCORNERS)
if FILTERDIM == '2D':
if RANKFILTER != 'NONE':
# apply filter
log.log(LogLevel.INFO, 'Apply 2D Filter : ' + RANKFILTER)
imp = FilterTools.apply_filter(imp,
radius=RADIUS,
filtertype=RANKFILTER)
if FILTERDIM == '3D':
if FILTER3D != 'NONE':
# apply filter
log.log(LogLevel.INFO, 'Apply 3D Filter : ' + FILTER3D)
imp = FilterTools.apply_filter3d(imp,
radiusx=RADIUSX,
radiusy=RADIUSY,
radiusz=RADIUSZ,
filtertype=FILTER3D)
if THRESHOLD != 'NONE':
# apply threshold
log.log(LogLevel.INFO, 'Apply Threshold : ' + THRESHOLD)
log.log(LogLevel.INFO, 'Correction Factor : ' + str(CORRFACTOR))
imp = ThresholdTools.apply_threshold(imp,
method=THRESHOLD,
background_threshold='dark',
stackopt=TH_STACKOPT,
corrf=CORRFACTOR)
# imp_t = imp.duplicate()
# imp_t.show("Threshold")
if FILL_HOLES:
# 3D fill holes
log.log(LogLevel.INFO, '3D Fill Holes ...')
imp = Reconstruction3D.fillHoles(imp.getImageStack())
if not FILL_HOLES:
imp = imp.getImageStack()
if WATERSHED:
# run watershed on stack
weights = ChamferWeights3D.BORGEFORS.getFloatWeights()
normalize = True
dynamic = 2
connectivity = LABEL_CONNECT
log.log(LogLevel.INFO, 'Run Watershed to separate particles ...')
#dist = BinaryImages.distanceMap(imp.getImageStack(), weights, normalize)
dist = BinaryImages.distanceMap(imp, weights, normalize)
Images3D.invert(dist)
#imp = ExtendedMinimaWatershed.extendedMinimaWatershed(dist, imp.getImageStack(), dynamic, connectivity, 32, False )
imp = ExtendedMinimaWatershed.extendedMinimaWatershed(
dist, imp, dynamic, connectivity, 32, False)
# extend borders
log.log(LogLevel.INFO, 'Border Extension ...')
# create BorderManager and add Zeros in all dimensions
bmType = BorderManager3D.Type.fromLabel("BLACK")
bm = bmType.createBorderManager(imp)
#bm = bmType.createBorderManager(imp.getStack())
BorderExt = ExtendBordersPlugin()
# extend border by always exb
#imp = BorderExt.process(imp.getStack(), EXB, EXB, EXB, EXB, EXB, EXB, bm)
imp = BorderExt.process(imp, EXB, EXB, EXB, EXB, EXB, EXB, bm)
# convert back to ImgPlus
pastack = ImagePlus('Particles', imp)
# check for pixel in 3d by size
log.log(LogLevel.INFO,
'Filtering VoxelSize - Minimum : ' + str(MINVOXSIZE))
pastack = BinaryImages.volumeOpening(pastack.getStack(), MINVOXSIZE)
imp = ImagePlus('Particles Filtered', pastack)
pastack = BinaryImages.componentsLabeling(imp, LABEL_CONNECT,
LABEL_BITDEPTH)
# get the labels
labels = LabelImages.findAllLabels(pastack)
log.log(LogLevel.INFO, 'Labels Filtered : ' + str(len(labels)))
# run 3D particle analysis
log.log(LogLevel.INFO, '3D Particle Analysis ...')
PA3d = ParticleAnalysis3DPlugin()
results = PA3d.process(pastack)
# colorize the labels
if LABEL_COLORIZE:
log.log(LogLevel.INFO, 'Colorize Lables ...')
#maxLabel = 255
maxLabel = len(labels)
bgColor = Color.BLACK
shuffleLut = True
lutName = CommonLabelMaps.GOLDEN_ANGLE.getLabel()
# Create a new LUT from info in dialog
lut = CommonLabelMaps.fromLabel(lutName).computeLut(
maxLabel, shuffleLut)
# Create a new RGB image from index image and LUT options
pastack_rgb = LabelImages.labelToRgb(pastack, lut, bgColor)
# convert to rgb color
IJ.run(pastack_rgb, "RGB Color", "slices")
if LABEL_COLORIZE:
return pastack_rgb, results, labels
elif not LABEL_COLORIZE:
return pastack, results, labels
def run(imagefile,
outputpath_orig,
convert_orig2copy=False,
sft='ome.tiff',
fillholes=True,
watershed=True,
watershed_connectivity=6,
verbose=True):
print fillholes, watershed, watershed_connectivity
# Opening the image
log.info('Opening Image: ' + imagefile)
# stitch togehter tiles
stitchtiles = True
# when set to True the number of pyramid levels can be read
setflatres = True
# select the desired pyramid level - level=0 for full resolution
readpylevel = 0
setconcat = True
openallseries = True
showomexml = False
attach = False
autoscale = True
# read the image
imp, MetaInfo = ImportTools.openfile(imagefile,
stitchtiles=stitchtiles,
setflatres=setflatres,
readpylevel=readpylevel,
setconcat=setconcat,
openallseries=openallseries,
showomexml=showomexml,
attach=attach,
autoscale=autoscale)
if verbose:
for k, v in MetaInfo.items():
log.info(str(k) + ' : ' + str(v))
if EXTRACT_CHANNEL:
imp = MiscTools.splitchannel(imp, CHINDEX)
# optional filtering
if FILTERTYPE != 'NONE':
log.info('Apply Filter : ' + FILTERTYPE)
imp = FilterTools.apply_filter(imp,
radius=FILTER_RADIUS,
filtertype=FILTERTYPE)
# apply threshold
log.info('Apply Threshold ...')
imp = ThresholdTools.apply_threshold(imp,
method=THRESHOLD_METHOD,
background_threshold=THRESHOLD_BGRD,
stackopt=THRESHOLD_STACKOPTION)
print "3D: ", MetaInfo['is3d']
# fill holes
if fillholes:
imp = BinaryTools.fill_holes(imp, is3d=MetaInfo['is3d'])
if watershed:
imp = WaterShedTools.run_watershed(
imp,
mj_normalize=True,
mj_dynamic=1,
mj_connectivity=watershed_connectivity,
is3d=MetaInfo['is3d'])
return imp
def run(imagefile):
# open image file and get a specific series
#imps, MetaInfo = ImportTools.openfile(imagefile)
imp, MetaInfo = ImportTools.openfile(imagefile,
stitchtiles=True,
setflatres=False,
readpylevel=PYLEVEL,
setconcat=True,
openallseries=True,
showomexml=False,
attach=False,
autoscale=True)
# Opening the image
log.info('Opening Image: ' + imagefile)
log.info('File Extension : ' + MetaInfo['Extension'])
if 'ResolutionCount' in MetaInfo:
log.info('Resolution Count : ' + str(MetaInfo['ResolutionCount']))
if 'SeriesCount' in MetaInfo:
log.info('SeriesCount : ' + str(MetaInfo['SeriesCount']))
# get sprecifies image series
#log.info('Getting Image Series : ' + str(IMAGESERIES))
#imp = ImageTools.getseries(imps, series=IMAGESERIES)
# do the processing
log.info('Start Processing ...')
if BINFACTOR == 1:
imp_p = imp
elif BINFACTOR >= 2:
# apply binning to reduce the image size
log.info('Apply Binning: ' + str(BINFACTOR) + ' Method : ' + BINMETHOD)
imp_p = MiscTools.apply_binning(imp,
binning=BINFACTOR,
method=BINMETHOD)
# apply filter
log.info('Apply Filter: ' + RANKFILTER)
imp_p = FilterTools.apply_filter(imp_p, radius=RADIUS)
# convert to 8-bit for the thresholding
log.info('Convert to 8-bit ...')
IJ.run(imp_p, "8-bit", "")
# apply threshold
log.info('Apply Threshold: ' + THRESHOLD)
imp_p = ThresholdTools.apply_threshold(imp_p,
method=THRESHOLD,
background_threshold=THRESHOLD_BGRD,
corrf=CORRFACTOR)
pastack, results = AnalyzeTools.analyzeParticles(imp_p,
MINSIZE,
MAXSIZE,
MINCIRC,
MAXCIRC,
filename=imagefile,
addROIManager=ROIS)
# apply suitable LUT to visualize detected particles
pastack = ImagePlus('Particles', pastack)
IJ.run(pastack, 'glasbey_inverted', '')
IJ.run(pastack, 'Enhance Contrast', 'saturated=0.35')
return pastack, results
clij.op().automaticThreshold(input, output, threshold_method)
# show result
clij.pull(output).show()
IJ.setMinAndMax(0, 1)
end = time.clock()
log.info('Duration of Processing CLIJ: ' + str(end - start))
threshold_stackoption = True
threshold_background = 'dark'
threshold_corr = 1.0
start2 = time.clock()
log.info('Apply Threshold ...')
th_image = ThresholdTools.apply_threshold(imp,
method=threshold_method,
background_threshold="dark",
stackopt=threshold_stackoption,
corrf=threshold_corr)
end2 = time.clock()
log.info('Duration of Processing Fiji: ' + str(end2 - start2))
# finish
log.info('Done.')
th_image.show()
def run(imagefile, outputpath_orig, convert_orig2copy=False,
sft='ome.tiff',
verbose=False):
# Opening the image
log.info('Opening Image: ' + imagefile)
# stitch togehter tiles
stitchtiles = True
# when set to True the number of pyramid levels can be read
setflatres = True
# select the desired pyramid level - level=0 for full resolution
readpylevel = 0
setconcat = True
openallseries = True
showomexml = False
attach = False
autoscale = True
# read the image
imp, MetaInfo = ImportTools.openfile(imagefile,
stitchtiles=stitchtiles,
setflatres=setflatres,
readpylevel=readpylevel,
setconcat=setconcat,
openallseries=openallseries,
showomexml=showomexml,
attach=attach,
autoscale=autoscale)
if convert_orig2copy:
log.info('Detected Extension : ' + MetaInfo['Extension'])
# check if it was already an OME-TIFF based on the file extension
ft = ['.ome.tif', '.ome.tiff']
if MetaInfo['Extension'] in ft:
"""
# just copy the original file
new_path = '/output/' + os.path.basename(imagefile)
command = 'cp ' + imagefile + ' ' + new_path
log.info('Copy Original file without conversion to output folder')
os.popen(command)
"""
# just copy the original file
new_path = '/output/' + os.path.basename(IMAGEPATH)
copy_ok = copyorig(IMAGEPATH, new_path, force_overwrite=True)
log.info(copy_ok)
if MetaInfo['Extension'] not in ft:
log.info('Converting original to OME-TIFF and save to output folder.')
savepath_orig = ExportTools.savedata(imp,
outputpath_orig,
extension=sft,
replace=True)
log.info('Saving converted original image : ' + savepath_orig)
if verbose:
for k, v in MetaInfo.items():
log.info(str(k) + ' : ' + str(v))
# do the processing
log.info('Start Processing ...')
if EXTRACT_CHANNEL:
imp = MiscTools.splitchannel(imp, CHINDEX)
# correct background
if CORRECT_BACKGROUND:
log.info('Removing Background using Rolling Ball ...')
imp = FilterTools.apply_rollingball(imp,
radius=RB_RADIUS,
createBackground=CREATEBACKGROUND,
lightBackground=LIGHTBACKGROUND,
useParaboloid=USEPARABOLOID,
doPresmooth=DOPRESMOOTH,
correctCorners=CORRECTCORNERS)
# optional filtering
if FILTERTYPE != 'NONE':
log.info('Apply Filter : ' + FILTERTYPE)
imp = FilterTools.apply_filter(imp,
radius=FILTER_RADIUS,
filtertype=FILTERTYPE)
# apply threshold
log.info('Apply Threshold ...')
imp = ThresholdTools.apply_threshold(imp,
method=THRESHOLD_METHOD,
background_threshold=THRESHOLD_BGRD,
stackopt=THRESHOLD_STACKOPTION)
#ip = imp.getProcessor()
#ip = ip.convertToByte(False)
#imp.setProcessor(ip)
#ImageConverter.setDoScaling(False)
#ImageConverter(imp).convertToGray8()
#imp.show()
#ImageConverter.setDoScaling(True);
#IJ.run(imp, "8-bit", "");
#IJ.run(imp, "Enhance Contrast", "saturated=0.35");
"""
# run watershed on stack
weights = ChamferWeights3D.BORGEFORS.getFloatWeights()
normalize = True
dynamic = 2
connectivity = 26
ImageConverter(imp).convertToGray8()
try:
dist = BinaryImages.distanceMap(imp, weights, normalize)
except:
dist = BinaryImages.distanceMap(imp.getImageStack(), weights, normalize)
Images3D.invert(dist)
#imp = ExtendedMinimaWatershed.extendedMinimaWatershed(dist, imp.getImageStack(), dynamic, connectivity, 32, False )
try:
imp = ExtendedMinimaWatershed.extendedMinimaWatershed(dist, imp, dynamic, connectivity, 32, False)
except:
imp = ExtendedMinimaWatershed.extendedMinimaWatershed(dist, imp.getImageStack(), dynamic, connectivity, 32, False)
"""
"""
pastack, results = AnalyzeTools.analyzeParticles(imp, MINSIZE, MAXSIZE, MINCIRC, MAXCIRC,
filename=imagefile,
addROIManager=ROIS)
# apply suitable LUT to visualize particles
pastack = ImagePlus('Particles', pastack)
IJ.run(pastack, 'glasbey_inverted', '')
IJ.run(pastack, 'Enhance Contrast', 'saturated=0.35')
return imp, pastack, results
"""
return imp