Multimodal Neural Operators for Real-Time Biomechanical Modelling of Traumatic Brain Injury

ArXi:2510.03248v3 Announce Type: replace-cross Background: Traumatic brain injury modeling requires integrating volumetric neuroimaging, graphic parameters, and acquisition metadata. Finite element solvers are too computationally expensive for clinical settings. Neural operators offer much faster inference. Their ability to integrate volumetric imaging with scalar metadata remains underexplored for biomechanical predictions. Objective: This study evaluates multimodal neural operator architectures for brain biomechanics.