Abstract #2392

NiGSP: Graph Signal Processing on multimodal MRI data.

Stefano Moia^1,2, Julia Brügger^1,3, Philip Egger^1,3, Giorgia Giulia Evangelista^1,3, Friedhelm Cristoph Hummel^1,3,4, Maria Giulia Preti^1,2, and Dimitri Van De Ville^1,2

¹Neuro-X Institute, Ecole polytechnique fédérale de Lausanne, Geneva, Switzerland, ²Department of Radiology and Medical Informatics (DRIM), Faculty of Medicine, University of Geneva, Geneva, Switzerland, ³Neuro-X Institute, EPFL Valais, Clinique Romande de Réadaptation, Sion, Switzerland, ⁴Department of Clinical Neurosciences, Geneva University Hospital (HUG), Geneva, Switzerland

Synopsis

Keywords: Software Tools, Brain ConnectivityNiGSP is a python-based toolbox aimed at facilitating the adoption of graph signal processing with an emphasis on multimodal brain imaging data. We present its standard workflow, that allows basic filtering operations and metrics computations, and we introduce a novel application to cerebral stroke consisting in the creation of a subject-specific anatomical lesion-based filter to be applied on functional MRI timeseries.

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