def get_no_nuclei_fully_enclosed(roi, full_nuclei_imp, overlap_threshold=0.65):
"""for a given cell roi and ImagePlus with binary nuclei, return how many nuclei lie ENTIRELY within the cell"""
bbox = roi.getBounds()
full_nuclei_imp.setRoi(roi)
cropped_nuc_imp = full_nuclei_imp.crop()
roi.setLocation(0, 0)
cropped_nuc_imp.setRoi(roi)
cropped_nuc_imp.killRoi()
roim = RoiManager(False)
mxsz = cropped_nuc_imp.getWidth() * cropped_nuc_imp.getHeight()
pa = ParticleAnalyzer(
ParticleAnalyzer.ADD_TO_MANAGER, ParticleAnalyzer.AREA
| ParticleAnalyzer.SLICE | ParticleAnalyzer.CENTROID, None, 0, mxsz)
pa.setRoiManager(roim)
pa.analyze(cropped_nuc_imp)
cell_imp = IJ.createImage("Cell binary", cropped_nuc_imp.getWidth(),
cropped_nuc_imp.getHeight(), 1, 8)
IJ.run(cell_imp, "Select All", "")
IJ.run(cell_imp, "Set...", "value=0 slice")
cell_imp.setRoi(roi)
IJ.run(cell_imp, "Set...", "value=255 slice")
no_enclosed_nuclei = 0
for idx, nuc_roi in enumerate(roim.getRoisAsArray()):
test_imp = Duplicator().run(cell_imp)
test_imp.setRoi(nuc_roi)
IJ.run(test_imp, "Set...", "value=255 slice")
test_imp.killRoi()
IJ.run(test_imp, "Create Selection", "")
IJ.run(test_imp, "Make Inverse", "")
test_roi = test_imp.getRoi()
test_roi_stats = test_roi.getStatistics()
cell_roi_stats = roi.getStatistics()
nuc_roi_stats = nuc_roi.getStatistics()
if test_roi_stats.area < (
cell_roi_stats.area +
(1 - overlap_threshold) * nuc_roi_stats.area
): # i.e. if more than (100*overlap_threshold)% of nucleus is inside cell...
no_enclosed_nuclei += 1
test_imp.changes = False
test_imp.close()
roi.setLocation(bbox.getX(), bbox.getY())
cropped_nuc_imp.changes = False
cropped_nuc_imp.close()
cell_imp.changes = False
cell_imp.close()
return no_enclosed_nuclei
def do_angular_projection(imp,
max_r_pix=60,
min_r_pix=10,
generate_roi_stack=True):
"""perform ray-based projection of vessel wall, c.f. ICY TubeSkinner (Lancino 2018)"""
Prefs.blackBackground = True
print("do angular projection input imp = " + str(imp))
split_chs = ChannelSplitter().split(imp)
mch_imp = split_chs[0]
IJ.setAutoThreshold(mch_imp, "IsoData dark stack")
egfp_imp = split_chs[1]
proj_imp = Duplicator().run(egfp_imp)
cl_imp = split_chs[2]
if generate_roi_stack:
egfp_imp_disp = Duplicator().run(egfp_imp)
roi_stack = IJ.createImage("rois", egfp_imp.getWidth(),
egfp_imp.getHeight(), egfp_imp.getNSlices(),
16)
centres = []
projected_im_pix = []
ring_rois = []
for zidx in range(cl_imp.getNSlices()):
if ((zidx + 1) % 100) == 0:
print("Progress = " +
str(round(100 * (float(zidx + 1) / cl_imp.getNSlices()))))
projected_im_row = []
proj_imp.setZ(zidx + 1)
mch_imp.setZ(zidx + 1)
bp = mch_imp.createThresholdMask()
bp.dilate()
bp.erode()
bp.erode()
bp.erode()
mask_imp = ImagePlus("mask", bp)
IJ.run(mask_imp, "Create Selection", "")
roi = mask_imp.getRoi()
proj_imp.setRoi(roi)
IJ.run(proj_imp, "Set...", "value=0 slice")
IJ.run(proj_imp, "Make Inverse", "")
roi = proj_imp.getRoi()
centre = (roi.getStatistics().xCentroid, roi.getStatistics().yCentroid)
centres.append(centre)
ring_roi_xs = []
ring_roi_ys = []
for theta in range(360):
pt1 = (centre[0] + min_r_pix * math.cos(math.radians(theta)),
centre[1] + min_r_pix * math.sin(math.radians(theta)))
pt2 = (centre[0] + max_r_pix * math.cos(math.radians(theta)),
centre[1] + max_r_pix * math.sin(math.radians(theta)))
roi = Line(pt1[0], pt1[1], pt2[0], pt2[1])
proj_imp.setRoi(roi)
profile = roi.getPixels()
projected_im_row.append(max(profile))
try:
ring_roi_xs.append(roi.getContainedPoints()[profile.index(
max(profile))].x)
except IndexError:
ring_roi_xs.append(pt2[0])
try:
ring_roi_ys.append(roi.getContainedPoints()[profile.index(
max(profile))].y)
except IndexError:
ring_roi_ys.append(pt2[1])
proj_imp.killRoi()
ring_roi = PolygonRoi(ring_roi_xs, ring_roi_ys, Roi.FREELINE)
ring_rois.append(ring_roi)
if generate_roi_stack:
roi_stack.setZ(zidx + 1)
roi_stack.setRoi(ring_roi)
IJ.run(roi_stack, "Line to Area", "")
IJ.run(
roi_stack, "Set...",
"value=" + str(roi_stack.getProcessor().maxValue()) + " slice")
#egfp_imp.setRoi(ring_roi);
projected_im_pix.append(projected_im_row)
# for ch in split_chs:
# ch.close();
out_imp = ImagePlus(
"projected", FloatProcessor([list(x) for x in zip(*projected_im_pix)]))
if generate_roi_stack:
roi_stack.show()
egfp_imp_disp.show()
# merge?
else:
roi_stack = None
return out_imp, roi_stack, ring_rois, centres
def generate_background_rois(input_mask_imp,
params,
membrane_edges,
dilations=5,
threshold_method=None,
membrane_imp=None):
"""automatically identify background region based on auto-thresholded image, existing membrane edges and position of midpoint anchor"""
if input_mask_imp is None and membrane_imp is not None:
segmentation_imp = Duplicator().run(membrane_imp)
# do thresholding using either previous method if threhsold_method is None or using (less conservative?) threshold method
if (threshold_method is None
or not (threshold_method in params.listThresholdMethods())):
mask_imp = make_and_clean_binary(segmentation_imp,
params.threshold_method)
else:
mask_imp = make_and_clean_binary(segmentation_imp,
threshold_method)
segmentation_imp.close()
else:
input_mask_imp.killRoi()
mask_imp = Duplicator().run(input_mask_imp)
rois = []
IJ.setForegroundColor(0, 0, 0)
roim = RoiManager(True)
rt = ResultsTable()
for fridx in range(mask_imp.getNFrames()):
mask_imp.setT(fridx + 1)
# add extra bit to binary mask from loaded membrane in case user refined edges...
# flip midpoint anchor across the line joining the two extremes of the membrane,
# and fill in the triangle made by this new point and those extremes
poly = membrane_edges[fridx].getPolygon()
l1 = (poly.xpoints[0], poly.ypoints[0])
l2 = (poly.xpoints[-1], poly.ypoints[-1])
M = (0.5 * (l1[0] + l2[0]), 0.5 * (l1[1] + l2[1]))
Mp1 = (params.manual_anchor_midpoint[0][0] - M[0],
params.manual_anchor_midpoint[0][1] - M[1])
p2 = (M[0] - Mp1[0], M[1] - Mp1[1])
new_poly_x = list(poly.xpoints)
new_poly_x.append(p2[0])
new_poly_y = list(poly.ypoints)
new_poly_y.append(p2[1])
mask_imp.setRoi(PolygonRoi(new_poly_x, new_poly_y, PolygonRoi.POLYGON))
IJ.run(mask_imp, "Fill", "slice")
mask_imp.killRoi()
# now dilate the masked image and identify the unmasked region closest to the midpoint anchor
ip = mask_imp.getProcessor()
dilations = 5
for d in range(dilations):
ip.dilate()
ip.invert()
mask_imp.setProcessor(ip)
mxsz = mask_imp.getWidth() * mask_imp.getHeight()
pa = ParticleAnalyzer(
ParticleAnalyzer.ADD_TO_MANAGER | ParticleAnalyzer.SHOW_PROGRESS,
ParticleAnalyzer.CENTROID, rt, 0, mxsz)
pa.setRoiManager(roim)
pa.analyze(mask_imp)
ds_to_anchor = [
math.sqrt((x - params.manual_anchor_midpoint[0][0])**2 +
(y - params.manual_anchor_midpoint[0][1])**2)
for x, y in zip(
rt.getColumn(rt.getColumnIndex("X")).tolist(),
rt.getColumn(rt.getColumnIndex("Y")).tolist())
]
if len(ds_to_anchor) > 0:
roi = roim.getRoi(ds_to_anchor.index(min(ds_to_anchor)))
rois.append(roi)
else:
rois.append(None)
roim.reset()
rt.reset()
roim.close()
mask_imp.close()
return rois
