[Matching of brain sections based on fourier descriptors]

We developed an algorithm based on Fourier Descriptors(FD) to match brain sections and specially aimed to pool electro-physiological data from individual animals and composite the results on a single brain. To test this algorithm, curvilinear features were first extracted from each section image of the midbrain of the rat resulting in three closed boundaries. A set of boundaries of 38 consecutive sections was then taken as standard templates for matching with any other brain sections processed in a similar way. Each section was represented by Fourier descriptors of these boundaries. Matching was done by minimizing the similarity function between an experimental brain section and the set of standard templates. This algorithm has been successfully used for the study of functional organization of AM-sound sensitive auditory neurons in the midbrain.