Sample image and/or code
image type EM image.
I want to try if it is possible to detect single synaptic vesicles from electron microscope (EM) images.
I used the cell density counting algorithm as a first step to try to detect synaptic vesicles from electron microscope images (since they are fairly homogeneous in shape and size).
I trained it and then I tested on another image by creating and exporting a probability map for that other image.
To distinguish the single objects I then turned to the object classification workload and uploaded the probability map along with the raw image. As far as I understood the following step would be to binarize the image using the Threshold and Size Filter “function”. I tried it but it didn’t work. Since I am familiar with Pyhton I loaded the probability map there and noticed that the pixel values (0-1 range) were very, very low, with the maximum one being just above 0.005. Since, as far as I understood, I can turn down the threshold to a minimum value of 0.01 it is likely that the reason why the threshold is not having any effect on the probability map is that it is above the maximum value of it. Am I right or am I missing something? If my hypothesis is true, is there nevertheless a way to get the image binarized with Ilastik despite the very low pixel values? Could the relatively low signal-to-noise ratio of EM images be the reason of the very low values?
Thanks a lot for any feedback