– S. Takerkart (LIF) : Learning from structured fMRI patterns using graph kernels Quand 27 septembre 2012 Ajouter au Calendrier Télécharger ICS Calendrier Google iCalendar Office 365 Outlook Live Learning from structured fMRI patterns using graph kernels. By Sylvain Takerkart, LIF. Classification of medical images in multi-subjects settings is a difficult challenge due to the variability that exists between individuals. Here we introduce a new graph-based framework specifically designed to deal with inter-subject functional variability present in functional MRI data. A graphical representation is built to encode the functional, geometric and structural properties of local activation patterns. The design of a specific graph kernel allows to conduct SVM classification directly in graph space. I will present results obtained on both simulated and real datasets, describe potential applications and discuss future directions for this work.
– S. Takerkart (LIF) : Learning from structured fMRI patterns using graph kernels Quand 27 septembre 2012 Ajouter au Calendrier Télécharger ICS Calendrier Google iCalendar Office 365 Outlook Live Learning from structured fMRI patterns using graph kernels.\nBy Sylvain Takerkart, LIF.\n\nClassification of medical images in multi-subjects settings is a difficult challenge due to the variability that exists between individuals. Here we introduce a new graph-based framework specifically designed to deal with inter-subject functional variability present in functional MRI data. A graphical representation is built to encode the functional, geometric and structural properties of local activation patterns. The design of a specific graph kernel allows to conduct SVM classification directly in graph space. I will present results obtained on both simulated and real datasets, describe potential applications and discuss future directions for this work.[
