def trackEnds(imageID, maskID):
index = RoiManager.getInstance2().getSelectedIndex()
inputIMP = WindowManager.getImage(imageID)
maskIMP = WindowManager.getImage(maskID)
points1 = inputIMP.getOverlay().get(0).getContainedPoints()[index]
points2 = inputIMP.getOverlay().get(1).getContainedPoints()[index]
roi = maskIMP.getOverlay().get(index)
outerBounds = roi.getBounds()
impMT, innerBounds = duplicateMaskInRoi(maskIMP, roi, True)
centroid = impMT.getOverlay().get(0).getContourCentroid()
nr, endPoint1, endPoint2 = findEndPointsInSkeleton(impMT)
track1 = trackEnd(impMT, endPoint1, centroid);
track2 = trackEnd(impMT, endPoint2, centroid);
impMT.changes=False
impMT.close()
newTrack1 = []
for point in track1:
newTrack1.append((point.x + outerBounds.x + innerBounds.x - 1,
point.y + outerBounds.y + innerBounds.y - 1))
newTrack2 = []
for point in track2:
newTrack2.append((point.x + outerBounds.x + innerBounds.x - 1,
point.y + outerBounds.y + innerBounds.y - 1))
track1X = [point[0] for point in newTrack1]
track1Y = [point[1] for point in newTrack1]
roiTrack1 = PolygonRoi(track1X, track1Y, Roi.POLYLINE)
inputIMP.getOverlay().add(roiTrack1)
track2X = [point[0] for point in newTrack2]
track2Y = [point[1] for point in newTrack2]
roiTrack2 = PolygonRoi(track2X, track2Y, Roi.POLYLINE)
inputIMP.getOverlay().add(roiTrack2)
inputIMP.repaintWindow()
def findEndPoints(imageID, maskID):
endPoints1 = []
endPoints2 = []
imp = IJ.getImage()
imp.setSlice(1);
roiManager = RoiManager.getInstance2()
rois = roiManager.getRoisAsArray()
roisToBeRemoved = []
index = 0
for roi in rois:
outerBounds = roi.getBounds()
impMT, innerBounds = duplicateMaskInRoi(imp, roi)
nr, endPoint1, endPoint2 = findEndPointsInSkeleton(impMT)
if (nr==2):
endPoint1.x = endPoint1.x + outerBounds.x + innerBounds.x - 1
endPoint1.y = endPoint1.y + outerBounds.y + innerBounds.y - 1
endPoint2.x = endPoint2.x + outerBounds.x + innerBounds.x - 1
endPoint2.y = endPoint2.y + outerBounds.y + innerBounds.y - 1
endPoints1.append(endPoint1)
endPoints2.append(endPoint2)
else:
roisToBeRemoved.append(index)
impMT.close()
index = index + 1
if (len(roisToBeRemoved)>0):
roiManager.setSelectedIndexes(roisToBeRemoved)
roiManager.runCommand("Delete")
roiManager.moveRoisToOverlay(WindowManager.getImage(maskID))
inputIMP = WindowManager.getImage(imageID)
inputIMP.setOverlay(PointRoi([seq.x for seq in endPoints1], [seq.y for seq in endPoints1]), Color.magenta, 1, Color.magenta)
otherPoints = PointRoi([seq.x for seq in endPoints2], [seq.y for seq in endPoints2])
otherPoints.setStrokeColor(Color.cyan)
otherPoints.setFillColor(Color.cyan)
inputIMP.getOverlay().add(otherPoints)
def process_image(imps, rois, ais_chno, nucleus_chno, bg_roino=3, sample_width=3, method='mean', dilations=3, average=1, threshold=0.1):
"""Opens a file and applies a Gaussian filter."""
orig_title = imps[ais_chno-1].getTitle()
print ",".join([i.getTitle() for i in imps])
print "Processing", orig_title
options = IS.MEAN | IS.MEDIAN # many others
nucleus_imp = imps[nucleus_chno-1].duplicate()
IJ.run(nucleus_imp, "Median...", "radius=10")
IJ.setAutoThreshold(nucleus_imp, "Default");
IJ.run(nucleus_imp, "Make Binary", "")
IJ.run(nucleus_imp, "Invert", "")
IJ.run(nucleus_imp, "Options...", "iterations=1 count=1 black do=Nothing");
IJ.run(nucleus_imp, "Watershed", "");
IJ.run(nucleus_imp, "Analyze Particles...", "size=20-Infinity clear add");
rm = RoiManager.getInstance2()
nuclei = rm.getRoisAsArray()
ais_imp = imps[ais_chno-1].duplicate()
print ais_imp.getTitle()
IJ.run(ais_imp, "8-bit","")
IJ.run(ais_imp, "Median...", "radius=1")
bg = 0
for i in range(bg_roino):
bg_roi = rois[i]
ais_imp.setRoi(bg_roi)
stats = ais_imp.getStatistics(options)
bg += stats.mean
print "Bg Roi %s, %s: %s" % (bg_roi.getName(), bg_roi, stats)
background = (int)(bg / bg_roino)
results = []
for i in range(bg_roino, len(rois)):
roiresult = {}
print i, rois[i].getName()
mimp = ais_imp.duplicate()
mimp.setTitle("%s-%s-AIS-Skeleton" % (orig_title, rois[i].getName()))
# IJ.run(mimp, "Median...", "radius=3")
mimp.setRoi(rois[i])
# IJ.setAutoThreshold(mimp, "Huang dark")
IJ.run(mimp, "Auto Local Threshold", "method=Phansalkar radius=15 parameter_1=0 parameter_2=0 white")
IJ.setBackgroundColor(0,0,0)
IJ.run(mimp, "Clear Outside", "")
Prefs.blackBackground = True
for j in range(dilations):
IJ.run(mimp, "Dilate", "")
IJ.run(mimp, "Skeletonize", "")
#IJ.run(mimp, "Analyze Skeleton (2D/3D)", "prune=none prune_0 calculate show display");
ais_skeleton, ais_points, points, orthogonals, ais_roi, nucleus_roi = create_skeleton(mimp, '%s-%s-AIS' % (orig_title, rois[i].getName()), nuclei_rois=nuclei, sample_width=sample_width)
if ais_skeleton is None:
print "Skipping -- AIS skeleton segmentation failed for ROI", rois[i].getName()
continue
#images['ais-skeleton-' + rois[i].getName()] = ais_skeleton
# subtract background
print "Subtracting background: bg=%d" % background
IJ.run(ais_imp, "Subtract...", "value=%d" % int(background))
ais_imp.setRoi(ais_roi)
ip = Straightener().straightenLine(ais_imp, sample_width)
straight_imp = ImagePlus('%s-%s-AIS-Straight' % (orig_title, rois[i].getName()), ip)
straight_imp.setCalibration(imps[ais_chno-1].getCalibration().copy())
IJ.run(straight_imp, "Green Fire Blue", "")
roiresult = {
'roi-name': rois[i].getName(),
'ais-image': straight_imp,
'ais-roi': ais_roi,
'nucleus-roi': nucleus_roi,
}
# plot
if len(points) > 1:
if method == 'sum':
threshold *= sample_width
plot, rt = create_plot(straight_imp, method, average, threshold=threshold)
roiresult['plot'] = plot
roiresult['table'] = rt
results.append(roiresult)
return results, background
