Adam, On Wed, Nov 20, 2013 at 7:44 AM, Adam Hughes <hughesadam87@gmail.com> wrote:
To download without an account, I am not familiar with any hosting solution, but if you guys have any recommendations I'd love to hear them.
Dropbox can be used for this... Thank you for you help, I will test out the methods you suggested
Is the goal only to count particles? In that case, I think a local thresholding (threshold_adaptive) would work on all these images. Then, just do a labelling (scipy.ndimage.label) and draw a histogram of particle sizes. You'll get a sharp peak around the true particle size, with bigger peaks for clumps. Once you have the mean particle size you can estimate the number of particles in each clump (barring occlusion in 3D, in which case you're stuffed anyway), and then the total number of particles in your image. Looking at your images, I don't think watershed (or anything else that I know) will do very well with the clumps. The contrast between adjacent particles is too low. Low-contrast-4 looks tricky... Are the smaller "points" particles of different sizes or just image noise? Finally, Watershed-f3 also looks hard, because it appears all the particles are touching... Again, I don't think watershed will help you here, nor anything else that doesn't have an a-priori knowledge of the particle size. Juan.