An enhanced sequential search feature selection based on mRMR to support FCD localization

Abstract

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.