SRC Biosciences has recently shown that automatic stereology can be achieved through a combination of deep learning, or more broadly machine learning, and unbiased stereology methods1-4.  Stereology users interested in participating should contact SRC Biosciences (src@disector.com). Equipment requirements are microscope with XYZ motorized stage, digital camera and PC running Windows 10.

  1. Mouton P.R., Phoulady HA, Goldgof D, Hall LO, Gordon M, Morgan D. Unbiased estimation of cell number using the automatic optical fractionator. J Chem Neuroanat. 80:1-8, 2017.
  2. Phoulady, H.A., Goldgof, D., Lawrence O. Hall, L.O., Mouton, P.R. Automatic Ground Truth for Deep Learning Stereology of Immunostained Neurons and Microglia in Mouse Neocortex. J. Chemical Neuroanat, 96: 1-7, 2019.
  3. Alahmari, S., Goldgof, D., Hall, D. Phoulady, H.A. Patel, R., Mouton, P.R. Automated Counts of Stained Cells by Deep Learning and Unbiased Stereology. J Chem Neuroanat, 96:94-101, 2019.
  4. Phoulady, H.A., Goldgof, D., Hall, L.O., Nash, K.N., Mouton, P.R. Automatic Stereology of Mean Nuclear Size of Neurons using an Active Contour Framework. J Chem Neuroanat, 96:110-115, 2019.