Reliable automated counting of Nissl-stained cells in tissue sections may be difficult, since even the best ImageJ plugins will have difficulties in performing the segmentation of individual cells. This may be much easier with a staining method based on staining the nucleus. I personally would use DAPI/Hoechst to stain all nuclei (independent of cell type) and e.g. NeuN to detect neuronal cell nuclei (dual staining). Both signals are restricted to the nucleus, so the segmentation algorithms of ImageJ will have no problems and you can perform automated counting very easily (please countercheck the results by manual counting). If you are more interested in morphological features like axonal branching etc the situation becomes much more difficult.
Completely agree with Just Genius, pay also attention do do not have to thick (cell overlapping) and too low resolution pictures which will complicate the analysis.
Thanks to sanil sharma, just genius and Nicolas Casadei
Dear Just
Do you have any easy and applicable protocol for DAPI/hoecht staining? Also which brand of trinuclear not costly microscope and camera do you all suggest to take the images?
Both DAPI qnd hoechst come from lifetech. I attached the protocol suggested. We also use NeuN MAB377 from Millipore which is really good and could be bought already labeled with Alexa Fluor.
We use a Ziess axioplan with a CCD Ziess 503 mono for fluorescence. Maybe you can ask lab around yours if any microscope is available for this purpose.
I have used DAPI/Hoechst to stain nuclei in thin neuronal cryosections, and then batch analyzed hundreds of images using a free program called CellProfiler. It will not only count the cells but also output other metrics such as area, diameter, roundness which may be useful for your study. I loved it the most for it's ability to batch process, so you can select your folder with all your images to analyze and then just leave it to run. From what I understand, I don't think ImageJ can do that.
I have also counted cells stained with DAPI and Neurotrace manually using ImageJ and the cell counter plugin. It works great as you can label cell types with different colors to keep track of them separately. You can also save the count and reload it later to continue from where you left off. You can also step through a stack of images and keep track across the whole depth of tissue.