Hi all,
I am working on particle analysis and I am trying to automate cell count. I came
up with an algorithm which first filters the noise , then does segmentation,
closes unclosed cells, fills holes and then does cell count. The algorithm
works well for some images, however there are problems when this code is applied
to images in which the cells are of the same clarity as the background.
Segmentation removes cells or part of the cells that are of the same contrast as
the background. I want to improve my algorithm to make sure all the cells are
correctly identified even if they are merged with the background or better
still if the cells can be adaptively segmented from the background. In other
words, I want a robust algorithm that works well with any image with good or bad
clarity.
Any suggestions will help me proceed further.
Thanks,
Sandhya
