<ul><li>A generative model for the mesh geometry of intracranial aneurysms (IA) called AneuG has been proposed to aid in predicting blood flow forces in real time.</li><li>Existing methods struggle to capture realistic IA features and ignore the relationship between IA pouches and parent vessels, limiting their physiological realism.</li><li>AneuG is a two-stage Variational Autoencoder (VAE)-based IA mesh generator that generates both aneurysm pouch shapes and parent vessels by utilizing Graph Harmonic Deformation (GHD) tokens.</li><li>The IA shape generation by AneuG can be conditioned to have specific morphological measurements, which can be beneficial for understanding shape variations in clinical studies and simulating the effects on fluid dynamics.</li></ul>

Two-Stage Generative Model for Intracranial Aneurysm Meshes with Morphological Marker Conditioning

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