Segmentation using Watershed would work to differentiate all cells (or the seeded watershed).
Differentiating both shapes could be done using a mask for each by fitting it and then counting n fits.

On Tuesday, 9 December 2014 20:58:43 UTC+1, Claiborne Morton wrote:
Hello Scikit community, 

I'm looking for help using particle descriptors to identify sickle cells in the attached image. As you can see the sickle cells are the long, thin cells. I have two issues, the first is that in some cases the sickle cells are in contact with other healthy cells. I am trying to find a way of separating (or water-shedding) the cells so that each "particle" is actually one cell. The second issue is that I am dealing with is trying to find shape descriptors that will allow me to accurately distinguish the sickle cells from the healthy cells. 

I used an eccentricity filter on the original image to remove all of the cells with eccentricity less than 0.6. Making this any higher results in removal of sickle cells. What other descriptors might be used for further differentiation?

Thanks, Clay