F.J. Theis, Z. Kohl, H.G. Kuhn, H.G. Stockmeier, and E.W. Lang (Germany)
Cell counting, image segmentation, cell classification, neurogenesis, BrdU
The genesis of new cells, especially of neurons, in the adult human brain is currently of great scientific interest. In or der to measure neurogenesis in animals new born cells are labelled with specific markers such as BrdU; in brain sec tions these can later be analyzed and counted through the microscope. So far, the image analysis has been performed by hand. In this work, we present an algorithm to auto matically segment the digital brain section picture into cell and noncell components, giving a count of the number of cells in the section. This is done by first training a so-called cell classifier with cell and non-cell patches in a supervised manner. This cell classifier can later be used in an arbitrary number of sections by scanning the section and choosing maxima of this classifier as cell center locations. For train ing, single- and multi-layer perceptrons were used. In pre liminary experiments, we get good performance of the clas sifier.
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