GSP-DERIVED BRAIN FEATURES FOR CLASSIFICATION IN ANXIETY AND DEPRESSION
Résumé
Anxiety and depression in adolescents are mental health conditions that negatively affect the quality of life. Our project aims to enhance our understanding of the biological mechanisms underlying those disorders by leveraging Graph Signal Processing (GSP) to integrate diffusion MRI and fMRI modalities. Here, we propose a classification pipeline based on the extraction of GSP-based measures to identify anxiety and depression features, using the Boston Adolescent Neuroimaging of Depression and Anxiety (BANDA) dataset.
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