An Enhanced Sequential Search Feature Selection Based on mRMR to Support FCD Localization

  • J. Castañeda-GonzalezEmail author
  • A. Alvarez-Meza
  • A. Orozco-Gutierrez
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11401)


One of the most common abnormalities that create a disorder in brain activity is the Focal Cortical Dysplasia (FCD), which can cause pharmacoresistant epilepsy. Patients with this kind of pathology can be treated surgically to remove the lesioned zone of the brain. However, the location of these lesions depends on the specialist expertise. Then, suitable support regarding the FCD analysis is required to minimize the localization subjectivity, primarily, for imbalance scenarios, e.g., few pathological regions are provided. In this work, we propose a new image processing approach to support FCD localization using a minimal redundancy maximal relevance-based feature selection stage that relies on a mutual information cost function to deal with imbalance problems. Then, our proposal finds a feature space through sequential searching aiming to highlight significant relationships between FCD labels and structural-based parameters from magnetic resonance brain images. Achieved results show a more significant improvement in terms of classifications statistics compared to state-of-the-art works.


Image processing Imbalance classification Feature selection 



Under grants provided by the project “Desarrollo de un sistema de apoyo al diagnóstico no invasivo de pacientes con epilepsia farmacoresistente asociada a displasias corticales cerebrales: método costo efectivo basado en procesamiento de imágenes de resonancia magnética” with code 111074455778 funded by COLCIENCIAS. J. Castañeda is partially funded by “Metodología para la segmentación automática de la corteza cerebral sobre imágenes MRI con base en características volumétricas usadas en técnicas de renderizado tridimensional por funciones de transferencia” by the Vicerrectoria de Investigación and the Maestría en ingeniría eléctrica program, both from the Universidad Tecnológica de Pereira.


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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • J. Castañeda-Gonzalez
    • 1
    Email author
  • A. Alvarez-Meza
    • 1
  • A. Orozco-Gutierrez
    • 1
  1. 1.Automatics Research GroupUniversidad Tecnológica de PereiraPereiraColombia

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