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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