I posted a few weeks ago about calibrating pixels to microns and successfully came up with a CalcuateMath to do the calculation in cp v2.
However, now I’m struggling with the IdentifyPrimaryObjects. I am working with surface brain tumor mets. I need to count the number and get an surface area output for each met in each image. The problem I am having is that im either over selecting the large tumors or if i increase the threshold correction im loosing some of the smaller mets. Additionally, I have had issues with oversegmentation and thus increased the size of the smoothing filter. However, when I do that, I also seem to loose some of the very small tumors.
At this point, I’m wondering if I’m using the wrong thresholding method. I also tried using the three class vs. the two class otsu and found that the threeclass was missing way too much or overselecting. Do I need to add an IlluminationCorrection? Or is there a better way to threshold the images.
I tried to attached some images and my current pipeline, however im not getting an error that the board attachment quota has been reached! Is there someone I could email images and my pipeline too?
Example images (I tried to upload)
ns1_3_cranial is selecting too much of the area around the large tumor
sdc1_11_cranial is missing some of the smaller tumor mets
ns1_13_caudal can be over segmented (the current pipeline settings seem to be handling it at this time)
ns1_4_cranial is an example of something with NO mets