White matter fiber tracking using diffusion magnetic resonance imaging (dMRI) provides a
noninvasive approach to map brain connections, but improving anatomical accuracy has …

Traumatic brain injury (TBI) is a global health concern. Mild TBI (mTBI) which accounts for
the majority of TBI cases, is hard to detect since often the imaging is normal but can still …

Finite element head (FE) models are important numerical tools to study head injuries and
develop protection systems. The generation of anatomically accurate and subject-specific …

Diffuse brain injuries are assessed with deformation-based criteria that utilize metrics based
on rotational head kinematics to estimate brain injury severity. Although numerous metrics …

Head injury models are notoriously time consuming and resource demanding in simulations,
which prevents routine application. Here, we extend a convolutional neural network (CNN) …

With the growing rate of traumatic brain injury (TBI), there is an increasing interest in
validated tools to predict and prevent brain injuries. Finite element models (FEM) are …

Background Head kinematics generated by laboratory reconstructions of professional
football helmet impacts have been applied to computational models to study the …

Head injury models are important tools to study concussion biomechanics but are
impractical for real-world use because they are too slow. Here, we develop a convolutional …

Successful validation of a head injury model is critical to ensure its biofidelity. However,
there is an ongoing debate on what experimental data are suitable for model validation …

Advanced neuroimaging provides new opportunities to enhance head injury models,
including the incorporation of white matter (WM) structural anisotropy. Information from high …