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AUTOMATIC CLASSIFICATION OF STRUCTURAL MRI FOR DIAGNOSIS OF NEURODEGENERATIVE DISEASES Acta biol.Colomb.
DÍAZ,GLORIA; ROMERO,EDUARDO; HERNÁNDEZ-TAMAMES,JUAN ANTONIO; MOLINA,VICENTE; MALPICA,NORBERTO.
This paper presents an automatic approach which classifies structural Magnetic Resonance images into pathological or healthy controls. A classification model was trained to find the boundaries that allow to separate the study groups. The method uses the deformation values from a set of regions, automatically identified as relevant, in a process that selects the statistically significant regions of a t-test under the restriction that this significance must be spatially coherent within a neighborhood of 5 voxels. The proposed method was assessed to distinguish healthy controls from schizophrenia patients. Classification results showed accuracy between 74% and 89%, depending on the stage of the disease and number of training samples.
Tipo: Info:eu-repo/semantics/article Palavras-chave: Neurodegenerative disease; Structural MRI; Pattern classification; SPM; VBM; DARTEL; Support vector machines.
Ano: 2010 URL: http://www.scielo.org.co/scielo.php?script=sci_arttext&pid=S0120-548X2010000300012
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