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| Natura: | Artículo científico |
| Lingua: | en |
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Universidad Nacional de Colombia
2013
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| Accesso online: | https://www.redalyc.org/articulo.oa?id=49626817004 |
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Sommario:
- Saliency-based characterization of group differences for magnetic resonance disease classification Andrea Rueda Fabio González Eduardo Romero Ingeniería Saliency maps Subject classification Visual Attention models Magnetic Resonance Imaging 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 diseasedsubjects. 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 usingsupport vector machines. The strategy’s performance was assessed on a set of 198 MR images extracted from the OASISdatabase and divided into four groups, reporting an average accuracy rate of and an average Equal Error Rate of . 2013 artículo científico 0012-7353 https://www.redalyc.org/articulo.oa?id=49626817004 en http://www.redalyc.org/revista.oa?id=496 Dyna application/pdf Universidad Nacional de Colombia Dyna (Colombia) Num.178 Vol.80