Open AccessBrain Tissue Classification to Detect Focal Cortical Dysplasia in Magnetic Resonance Imaging
Author(s) -
Fabricio Simozo,
Marcos Antônio de Oliveira,
Leonardo Murta
Publication year - 2020
Language(s) - English
Resource type - Conference proceedings
DOI - 10.5753/eniac.2020.12164
Subject(s) - cortical dysplasia , magnetic resonance imaging , cortex (anatomy) , epilepsy , voxel , artificial intelligence , pathology , medicine , neuroscience , computer science , pattern recognition (psychology) , psychology , radiology
Focal cortical dysplasia (FCD) is a local malformation of the cortex, the main cause of refractory epilepsy in childhood and one of the most common causes in adults. The surgery decision and planning depend on the FCD localization. Although recent studies have successfully detected FCD through artificial intelligence, no study investigates the relevance and prevalence of cortical features on FCD identification and the performance of different machine learning techniques. In this study, the proposed method constructed a voxel-based set of features, e.g., texture measure, border definition, cortical thickness.