Abstract

RUEDA, ANDREA; GONZALEZ, FABIO  and  ROMERO, EDUARDO. SALIENCY-BASED CHARACTERIZATION OF GROUP DIFFERENCES FOR MAGNETIC RESONANCE DISEASE CLASSIFICATION. Dyna rev.fac.nac.minas [online]. 2013, vol.80, n.178, pp.21-28. ISSN 0012-7353.

Anatomical variability of patient's brains limits the statistical analyses about presence or absence of a pathology. In this paper, we present an approach for classification of brain Magnetic Resonance (MR) images from healthy and diseased subjects. The approach builds up a saliency map, which extract regions of relative change in three different dimensions: intensity, orientation and edges. The obtained regions of interest are used as suitable patterns for subject classification using support vector machines. The strategy's performance was assessed on a set of 198 MR images extracted from the OASIS database and divided into four groups, reporting an average accuracy rate of 74.54% and an average Equal Error Rate of 0.725.

Keywords : Subject classification; Magnetic Resonance Imaging; Visual Attention models; Saliency maps.

        · abstract in Spanish     · text in English     · English ( pdf )