Issue with Identify Primary Object after Threshold

Image Analysis
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#1

Hi everyone!

I am using Cell Profiler to analyze levels of fluorescence intensity in one channel (red) within neurons, which are stained with NeuN in the green channel. To isolate neurons, I am applying the Threshold module to a grayscale image in the green channel, and then I use ‘IdentifyPrimaryObjects’ to outline the NeuN+ neurons. For most of my images, this system works very well. However, for a subset (perhaps 1/4 of them), which appear to be randomly distributed across my image samples, the IdentifyPrimaryObject module doesn’t identify any objects from the thresholded image, though the thresholding looks very similar between the ones that work and don’t work. The objects are within the size range and are well separated from each other, so I cannot understand why this process selectively works. I’m including the images of this identification step. I would appreciate any help understanding why this is not working for all of my images.

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Screen Shot 2020-12-20 at 7.42.49 PM
Screen Shot 2020-12-20 at 7.42.49 PM1282×1056 113 KB

#2

Hi @nr22,

I am not sure why it is not working in few of your image set. We may need a sample image to reproduce the issue. But,
To isolate neurons from your grayscale image, you can use directly “IdentifyPrimaryObject” module with has much more criteria to identify the objects . You can use the same thresholding parameters here that you use in “Threshold” module. This is similar to nuclei segmentation in Human Cells example.
Basically “Threshold” module identifies the pixels based on the threshold criteria & converts the image into binary image. So, if you want to use them further, no need of Primary object module rather you can use “ConvertImageToObject” module to have them as a individual objects.

Regards,
Lakshmi
www.wakoautomation.com