def showimage(self):
roim = RoiManager.getInstance()
if roim is None:
roim = RoiManager()
IJ.run("Close All")
IJ.run("Clear Results")
try:
roim.reset()
except AttributeError:
roim.runCommand("reset")
obj = self.fcsimages[self.idximg][0]
imgName = self.fcsimages[self.idximg][1]
img = BF.openImagePlus(imgName)[0]
img.setZ(obj[1][2]+1)
img.setC(3)
IJ.run(img, "Grays", "");
img.setC(1)
img.show()
#draw rois
for i in range(1, len(obj)+1):
PR = PointRoi(obj[i][0],obj[i][1])
try:
PR.setSize(3)
PR.setPointType(0)
roim.addRoi(PR)
except:
roim.addRoi(PR)
roim.runCommand('Show All with Labels')
def getSpots(imp, channel, detector_type, radius, threshold, overlay,
roi_type="large", roi_color=ColorRGB("blue")):
""" Performs the detection, adding spots to the image overlay
:imp: The image (ImagePlus) being analyzed
:channel: The target channel
:detector_type: A string describing the detector: "LoG" or "DoG"
:radius: Spot radius (NB: trackmate GUI accepts diameter)
:threshold: Quality cutoff value
:overlay: The image overlay to store spot (MultiPoint) ROIs
:roi_type: A string describing how spot ROIs should be displayed
:returns: The n. of detected spots
"""
settings = Settings()
settings.setFrom(imp)
settings.detectorFactory = (LogDetectorFactory() if "LoG" in detector_type
else DogDetectorFactory())
settings.detectorSettings = {
DK.KEY_DO_SUBPIXEL_LOCALIZATION: False,
DK.KEY_DO_MEDIAN_FILTERING: True,
DK.KEY_TARGET_CHANNEL: channel,
DK.KEY_RADIUS: radius,
DK.KEY_THRESHOLD: threshold,
}
trackmate = TrackMate(settings)
if not trackmate.execDetection():
lservice.error(str(trackmate.getErrorMessage()))
return 0
model = trackmate.model
spots = model.getSpots()
count = spots.getNSpots(False)
ch_id = "Spots Ch%d" % channel
if count > 0:
roi = None
cal = imp.getCalibration()
t_pos = imp.getT()
if (t_pos > 1):
lservice.warn("Only frame %d was considered..." % t_pos)
for spot in spots.iterable(False):
x = cal.getRawX(spot.getFeature(spot.POSITION_X))
y = cal.getRawY(spot.getFeature(spot.POSITION_Y))
z = spot.getFeature(spot.POSITION_Z)
if z == 0 or not cal.pixelDepth or cal.pixelDepth == 0:
z = 1
else:
z = int(z // cal.pixelDepth)
imp.setPosition(channel, z, t_pos)
if roi is None:
roi = PointRoi(int(x), int(y), imp)
else:
roi.addPoint(imp, x, y)
roi.setStrokeColor(colorRGBtoColor(roi_color))
if "large" in roi_type:
roi.setPointType(3)
roi.setSize(4)
else:
roi.setPointType(2)
roi.setSize(1)
overlay.add(roi, ch_id)
return count
def drawLines(imp, points=None):
if points and (len(points) % 2 == 0):
# points is numeric list of even length
pRoi = PointRoi(points[0::2], points[1::2], len(points) / 2)
pRoi.setShowLabels(True)
pRoi.setSize(3)
imp.setRoi(pRoi)
roi = imp.getRoi()
pp = roi.getFloatPolygon()
# print "Added", pp.npoints
if pp.npoints <= 1:
# don't draw if only one point
return
xys = []
for i in xrange(pp.npoints):
xys.append([pp.xpoints[i], pp.ypoints[i]])
ol = Overlay()
x0 = xys[0][0]
y0 = xys[0][1]
cal = imp.getCalibration()
for i in xrange(1, pp.npoints):
xi = xys[i][0]
yi = xys[i][1]
# prepare text label
d = math.sqrt((xi - x0)**2 + (yi - y0)**2) * cal.pixelWidth
dText = String.format("%.2f ", d) + cal.getUnits()
textOffset = 30
xt = xi
yt = yi
# if xi > x0:
# xt += textOffset
if xi < x0:
xt -= textOffset
# if yi > y0:
# yt += textOffset
if yi < y0:
yt -= textOffset
dTextRoi = TextRoi(xt, yt, dText)
ol.add(dTextRoi)
lineRoi = Line(x0, y0, xi, yi)
lineRoi.setStrokeWidth(1)
lineRoi.setStrokeColor(Color(255, 255, 0))
ol.add(lineRoi)
imp.setOverlay(ol)
imp.updateAndDraw()
def drawLines(imp, points=None):
if points and (len(points)%2 == 0):
# points is numeric list of even length
pRoi = PointRoi(points[0::2], points[1::2], len(points)/2)
pRoi.setShowLabels(True)
pRoi.setSize(3)
imp.setRoi(pRoi)
roi = imp.getRoi()
pp = roi.getFloatPolygon()
# print "Added", pp.npoints
if pp.npoints <= 1:
# don't draw if only one point
return
xys = []
for i in xrange(pp.npoints):
xys.append([pp.xpoints[i], pp.ypoints[i]])
ol = Overlay()
x0 = xys[0][0]
y0 = xys[0][1]
cal = imp.getCalibration()
for i in xrange(1, pp.npoints):
xi = xys[i][0]
yi = xys[i][1]
# prepare text label
d = math.sqrt((xi - x0)**2 + (yi - y0)**2) * cal.pixelWidth
dText = String.format("%.2f ", d) + cal.getUnits()
textOffset = 30
xt = xi
yt = yi
# if xi > x0:
# xt += textOffset
if xi < x0:
xt -= textOffset
# if yi > y0:
# yt += textOffset
if yi < y0:
yt -= textOffset
dTextRoi = TextRoi(xt, yt, dText)
ol.add(dTextRoi)
lineRoi = Line(x0, y0, xi, yi)
lineRoi.setStrokeWidth(1)
lineRoi.setStrokeColor(Color(255,255,0))
ol.add(lineRoi)
imp.setOverlay(ol)
imp.updateAndDraw()
def process_img(img_path):
IJ.log('Processing {} ...'.format(img_path))
# open image
imp = IJ.openImage(img_path)
imp.show()
w_big = imp.getWindow()
w_big.setLocationAndSize(1050, 400, 500, 500)
# read relative csv file rows (coordinates of centers)
img_name, img_extension = os.path.splitext(img_path)
marker_path = img_name + '.csv'
if not os.path.exists(marker_path):
root = os.path.dirname(marker_path)
IJ.log('Creating corrected CSV files in {}...'.format(root))
mrk.markers_to_csv(root, y_inv_height=imp.height)
markers = mrk.read_marker(marker_path, to_int=True)
for cs in gen_cell_stacks(imp, markers, cube_roi_dim, scaleZ):
# identify cell in original image
imp.setSlice(cs.seed[2] + 1)
point = PointRoi(cs.seed[0], cs.seed[1])
point.setSize(3)
point.setColor(Color.RED)
imp.setRoi(point)
if discard_margin_cells:
if not cs.onBorder:
process_cell(cs)
else:
IJ.log('Skipped on border cell in seed ' + str(cs.seed))
else:
process_cell(cs)
c = raw_input(
"Press enter to show the next cell or 'n' to go to the next image\n"
)
cs.close()
if c == 'n':
IJ.log("Skipped remaining cells")
break
def updatePointRoi(self):
# Surround with try/except to prevent blocking
# ImageJ's stack slice updater thread in case of error.
try:
# Update PointRoi
self.imp.killRoi()
point = self.nuclei[self.imp.getFrame()] # map 1-based slices
# to 0-based nuclei Z coords
if len(point) == 0:
return
IJ.log("Cell found in frame " + str(self.imp.getFrame()))
# New empty PointRoi for the current slice
roi = PointRoi(point[0], point[1])
# Style: large, red dots
roi.setSize(4) # ranges 1-4
roi.setPointType(2) # 2 is a dot (filled circle)
roi.setFillColor(Color.red)
roi.setStrokeColor(Color.red)
self.imp.setRoi(roi)
except:
IJ.error(sys.exc_info())
def updatePointRoi(self):
# Surround with try/except to prevent blocking
# ImageJ's stack slice updater thread in case of error.
try:
# Update PointRoi
self.imp.killRoi()
points = self.nuclei[
self.imp.getSlice() -
1] # map 1-based slices to 0-based nuclei Z coords
if 0 == len(points):
IJ.log("No points for slice " + str(self.imp.getSlice()))
return
roi = PointRoi()
# Style: large, red dots
roi.setSize(4) # ranges 1-4
roi.setPointType(2) # 2 is a dot (filled circle)
roi.setFillColor(Color.red)
roi.setStrokeColor(Color.red)
# Add points
for point in points: # points are floats
roi.addPoint(self.imp, int(point[0]), int(point[1]))
self.imp.setRoi(roi)
except:
IJ.error(sys.exc_info())
xmlfile = arg[0]
ch = 1
#open xml file and parse it
tree = ET.parse(xmlfile)
root = tree.getroot()
obj, imgName = getPosition(root)
print imgName
#open image
img = BF.openImagePlus(imgName)[0]
img.setZ(obj[1][2]+1)
img.setC(int(ch))
img.show()
#draw rois
for i in range(1, len(obj)+1):
PR = PointRoi(obj[i][0],obj[i][1])
try:
PR.setSize(3)
PR.setPointType(0)
roim.addRoi(PR)
except:
roim.addRoi(PR)
roim.runCommand('Show All with Labels')
def run():
mask_ip = impSkel.getProcessor()
part_ip = impPart.getProcessor()
if not mask_ip.isBinary():
error(impSkel.getTitle() + " is not a binary mask.")
return
# Mask grayscale image and skeletonize mask
try:
mask_pixels = mask_ip.getPixels()
part_pixels = part_ip.getPixels()
for i in xrange(len(part_pixels)):
if mask_pixels[i] == 0:
part_pixels[i] = 0
part_ip.setPixels(part_pixels)
except IndexError:
error("Chosen images are not the same size.")
skeletonize(impSkel)
# Get skeleton features
end_points, junctions, junction_voxels, total_len = skeleton_properties(impSkel)
if not end_points and not junction_voxels:
error(impSkel.getTitle() + " does not seem a valid skeleton.")
return
# Retrieve centroids from IJ1
threshold_lower = get_threshold(impPart, thres_method)
cx, cy, n_particles = get_centroids(impPart, threshold_lower)
if None in (cx, cy):
error("Verify parameters: No particles detected.")
return
# Loop through each centroids and categorize its position
# according to its distance to skeleton features
n_bp = n_tip = n_none = n_both = 0
overlay = cleanse_overlay(impPart.getOverlay())
for i in range(n_particles):
j_dist = ep_dist = sys.maxint
# Retrieve the distance between this particle and the closest junction voxel
for jvoxel in junction_voxels:
dist = distance(cx[i], cy[i], jvoxel.x, jvoxel.y)
if (dist <= cutoff_dist and dist < j_dist):
j_dist = dist
# Retrieve the distance between this particle and the closest end-point
for end_point in end_points:
dist = distance(cx[i], cy[i], end_point.x, end_point.y)
if (dist <= cutoff_dist and dist < ep_dist):
ep_dist = dist
roi_id = str(i).zfill(len(str(n_particles)))
roi_name = "Unknown:" + roi_id
roi_color = Color.ORANGE
roi_type = 2 # dot
# Is particle associated with neither junctions nor end-points?
if j_dist > cutoff_dist and ep_dist > cutoff_dist:
roi_name = "Unc:" + roi_id
#n_none += 1
# Is particle associated with both?
elif abs(j_dist - ep_dist) <= pixel_size(impPart) / 2:
roi_name = "J+T:" + roi_id
roi_color = Color.CYAN
#roi_type = 1 # crosshair
n_both += 1
# Is particle associated with an end-point?
elif ep_dist < j_dist:
roi_name = "Tip:" + roi_id
roi_color = Color.GREEN
#roi_type = 0 # hybrid
n_tip += 1
# Is particle associated with a junction?
elif ep_dist > j_dist:
roi_name = "Junction:" + roi_id
roi_color = Color.MAGENTA
#roi_type = 3 # circle
n_bp += 1
roi = PointRoi(cx[i], cy[i])
roi.setName(roi_name)
roi.setStrokeColor(roi_color)
roi.setPointType(roi_type)
roi.setSize(2) # medium
overlay.add(roi)
# Display result
impSkel.setOverlay(overlay)
impPart.setOverlay(overlay)
# Output some measurements
if "table" in output:
t = ResultsTable.getResultsTable() if "IJ1" in output else DefaultGenericTable()
addToTable(t, "Part. image", "%s (%s)" % (impPart.getTitle(), impPart.getCalibration().getUnits()))
addToTable(t, "Skel. image", "%s (%s)" % (impSkel.getTitle(), impSkel.getCalibration().getUnits()))
addToTable(t, "Junction particles", n_bp)
addToTable(t, "Tip particles", n_tip)
addToTable(t, "J+T particles", n_both)
addToTable(t, "Unc. particles", n_none)
addToTable(t, "Junctions w/ particles", n_bp + n_both)
addToTable(t, "Tips w/ particles", n_tip + n_both)
addToTable(t, "Total skel. lenght", total_len)
addToTable(t, "Total end points", len(end_points))
addToTable(t, "Total junctions", sum(junctions))
addToTable(t, "Unc. particles / Total skel. lenght)", n_none/total_len)
addToTable(t, "Snap-to dist.", str(cutoff_dist) + impPart.getCalibration().getUnits())
addToTable(t, "Threshold", "%d (%s)" % (threshold_lower, thres_method))
showTable(t, "Results")
def getSpots(imp,
channel,
detector_type,
radius,
threshold,
overlay,
roi_type="large",
roi_color=ColorRGB("blue")):
""" Performs the detection, adding spots to the image overlay
:imp: The image (ImagePlus) being analyzed
:channel: The target channel
:detector_type: A string describing the detector: "LoG" or "DoG"
:radius: Spot radius (NB: trackmate GUI accepts diameter)
:threshold: Quality cutoff value
:overlay: The image overlay to store spot (MultiPoint) ROIs
:roi_type: A string describing how spot ROIs should be displayed
:returns: The n. of detected spots
"""
settings = Settings()
settings.setFrom(imp)
settings.detectorFactory = (LogDetectorFactory() if "LoG" in detector_type
else DogDetectorFactory())
settings.detectorSettings = {
DK.KEY_DO_SUBPIXEL_LOCALIZATION: False,
DK.KEY_DO_MEDIAN_FILTERING: True,
DK.KEY_TARGET_CHANNEL: channel,
DK.KEY_RADIUS: radius,
DK.KEY_THRESHOLD: threshold,
}
trackmate = TrackMate(settings)
if not trackmate.execDetection():
lservice.error(str(trackmate.getErrorMessage()))
return 0
model = trackmate.model
spots = model.getSpots()
count = spots.getNSpots(False)
ch_id = "Spots Ch%d" % channel
if count > 0:
roi = None
cal = imp.getCalibration()
t_pos = imp.getT()
if (t_pos > 1):
lservice.warn("Only frame %d was considered..." % t_pos)
for spot in spots.iterable(False):
x = cal.getRawX(spot.getFeature(spot.POSITION_X))
y = cal.getRawY(spot.getFeature(spot.POSITION_Y))
z = spot.getFeature(spot.POSITION_Z)
if z == 0 or not cal.pixelDepth or cal.pixelDepth == 0:
z = 1
else:
z = int(z // cal.pixelDepth)
imp.setPosition(channel, z, t_pos)
if roi is None:
roi = PointRoi(int(x), int(y), imp)
else:
roi.addPoint(imp, x, y)
roi.setStrokeColor(colorRGBtoColor(roi_color))
if "large" in roi_type:
roi.setPointType(3)
roi.setSize(4)
else:
roi.setPointType(2)
roi.setSize(1)
overlay.add(roi, ch_id)
return count
