GSP-DERIVED BRAIN FEATURES FOR CLASSIFICATION IN ANXIETY AND DEPRESSION - Archive ouverte HAL
Communication Dans Un Congrès Année : 2024

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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Dates et versions

hal-04770983 , version 1 (07-11-2024)
hal-04770983 , version 2 (07-11-2024)

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  • HAL Id : hal-04770983 , version 2

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Sébastien Dam, Pierre Maurel, Julie Coloigner. GSP-DERIVED BRAIN FEATURES FOR CLASSIFICATION IN ANXIETY AND DEPRESSION. ISBI 2024 - 21st IEEE International Symposium on Biomedical Imaging, May 2024, Athens, Greece. ⟨hal-04770983v2⟩
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