The cerebral cortex is distinguished by layers of neurons of different
morphologies and densities. The layers are formed by the migration of
newly generated neurons from the ventricular zone to the cortical pla
te near the outer (pial) boundary of the cortex, along radial paths ap
proximately perpendicular to the cortical. surface, Immunochemical lab
elling makes these cells' patterns visible in brightfield microscopy s
o that layer formation can be studied, We developed a suite of program
s that automatically digitize the entire cortex, identify the labelled
cells and compute cell densities along local radial paths. Cell ident
ification used supervised classification on all the significantly stai
ned objects corresponding to maxima in lowpass filtered versions of th
e digital micrographs. Classification of all the stained objects as ce
lls or noncell objects was made by a decision rule based on morphometr
ic and grey-level texture features, including features based on Gabor
functions, Detection sensitivity and classification accuracy were join
tly maximized on training data consisting of about 3000 expert-identif
ied neurons in micrographs, Total program performance was tested on a
separate (test) set of labelled neurons the same size as the training
data set, The program detected 85% of the cells in the test set with a
total error of 0.19. The identified cells' locations were used to com
pute population densities along normals to the cortical layers, and th
ese densities served as a measure of neuronal migration. Transcortical
density profiles obtained by computation and by manual cell counting
were very similar, The cell identification program was built on well-e
stablished methods in statistical pattern recognition and image analys
is and should generalize readily to other histological preparations.