I am trying to do segmentation on several images of brain tissue that has gone through immunohistochemistry (IHC) for cfos in order to segment out the cfos cells to do a cell count.
I have cropped the image to contain only the brain region that I am interested in.
Two such images are shown.
As you can see from the two images, one is brighter than the other and in each image, some of the cfos cells are really dark whereas others are much lighter. Additionally, the background is not completely uniform. All things that might make segmentation more difficult.
Also shown is a small section from the first image with the cfos cells outlined.
I was working with the Weka in the hopes to segment the images, but I am running into problems being able to count both dark and light cells, and especially having a weka model that works on both darker and lighter images.
I tried preprocessing the images by duplicating the image, performing a gaussian blur with sigma = 5, and then subtracting the two images before doing weka. This seemed to work better, but then I had the obvious problem with the Weka thinking that the edge of the brain slice are cfos cells.
So, I am hoping for some suggestions on how to use the weka for this segmentation, what training features to use, preprocessing suggestions, or even a different application/approach altogether.
Thank you so much.