Hello! Is there any way to obtain the area of the positive detected cells? My cells are very irregular so the counts are not reliable.
Thank you!
Hello! Is there any way to obtain the area of the positive detected cells? My cells are very irregular so the counts are not reliable.
Thank you!
Hi @ic2396,
Do you mean the sum of all the areas of the positive cells in your image?
If so, something like this should work:
def sumArea = 0
getCellObjects().forEach {
if (it.getPathClass() == getPathClass("Positive"))
sumArea += it.getMeasurementList().getMeasurementValue("Cell: Area")
}
print "Total sum of all positive cells' area: " + sumArea + " (Don't forget the unit!)"
Hi Melvin,
I would like to get the area of positive cells in a specific annotation. I tried running your script, but the result is 0.
Yes, my script checks if the class of the cell is Positive
. If not, it will never add anything to sumArea
.
If you give more details about your image it will help see how to create a proper script for you:
It sounds like thereās only one annotation. If so, what is the class of the annotation (or anything else to distinguish it from other ones)?
I run positive cell detection (Nucleus: Channel 2 mean) in one annotation, then applied an object classifier labeling as Positive or Negative. In the detection measurement table, the class says either āPositive: Positiveā or āNegative: Negative.ā Then click save.
Currently I have multiple annotations, but only one contains the cells. The class of the annotation is āNoneā
Thank you!
Great thank you
You could then do this (I took the name of the annotation as criteria to filter out annotations):
def sumArea = 0
getAnnotationObjects().forEach { ann ->
if (ann.getName().equals("LacbSh 0.86 Left")) {
ann.getChildObjects().forEach {
if (it.getPathClass() == getPathClass("Positive: Positive"))
sumArea += it.getMeasurementList().getMeasurementValue("Cell: Area")
}
print "Total sum of all positive cells' area: " + sumArea + " (Don't forget the unit!)"
return
}
}
Hi Melvin, I just ran the new script, but I keep getting zero.
Mmh okā¦
What does it show when you run this:
getAnnotationObjects().forEach { ann ->
print ann.getName()
if (ann.getName().equals("LacbSh 0.86 Left")) {
ann.getChildObjects().forEach { cell ->
print cell.getPathClass()
}
}
}
I think there is definitely something wrong with the object classifier I run for that Image. Bc I tried your script in a different image with only positive cell detection and it worked perfectly.
When I run:
getAnnotationObjects().forEach { ann ->
print ann.getName()
if (ann.getName().equals("LacbSh 0.86 Left")) {
ann.getChildObjects().forEach { cell ->
print cell.getPathClass()
}
}
}
I get:
INFO: null
INFO: null
INFO: null
INFO: null
INFO: null
INFO: null
INFO: null
INFO: null
INFO: null
INFO: LacbSh 0.86 Left
INFO: Positive: Negative
INFO: Positive: Negative
INFO: Positive: Negative
INFO: Positive: Negative
INFO: Positive: Negative
INFO: Positive: Negative
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INFO: Negative: Negative
INFO: Negative: Negative
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Do you need the object classifier? āPositive cell detectionā already assigns cells as positive or negative. If you donāt want to use that, you can run āCell detectionā instead (or use Classify ā Object classification ā Reset detection classification).
Either way, I think you shouldnāt have classifications duplicated, i.e. just Positive
or Negative
ā rather than Positive: Positive
and Negative: Negative
.
Yes, from the output of the script I sent you, it looks like there are no cell with Positive: Positive
as classification. You do have other ones though (Positive: Negative
and Negative: Negative
)
The screenshot in your last post shows an annotation with no Positive detections either, I donāt know if thatās normal?
Have you tried to resolve the hierarchy and rerun the script:
resolveHierarchy()
Yep, I should have read this thread before responding to the other, but I think cleaning up the up-stream steps will be the most helpful. Or including a sample image and explaining what you want to accomplish, as requested in the initial posting
Also edited the above post due to scrolling and code legibility.