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Abstract #3751

An automatic classificator based on local fractal features for the identification of cortical malformations

Alberto De Luca 1,2 , Denis Peruzzo 2 , Fabio Triulzi 3 , Filippo Arrigoni 2 , and Alessandra Bertoldo 1

1 Department of Information Engineering, University of Padova, Padova, PD, Italy, 2 Department of Neuroimaging, Scientific Institute, IRCCS "Eugenio Medea", Bosisio Parini, LC, Italy, 3 Neuroradiology department, Scientific Institute, IRCCS "C Granda" - Ospedale Maggiore Policlinico, Milan, MI, Italy

Malformations of cortical development (MCDs) encompass a wide spectrum of brain abnormalities which extension and localization are extremely variable from subject to subject and their analysis with existing methods is difficult. First we extended a fractal geometry algorithm to compute voxelwise maps, then defined two distance maps used to quantify the distance of a single subject from a population. Results suggest that fractal values are sensible to the structural properties of the tissues being statistically different values between healthy and malformed cortex. The classification based on these indices is able to reveal malformed areas with high specificity.

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