Finite Element Head ModelPersonalization by Mesh Morphing

Sammanfattning: Finite Element (FE) head models are very convenient tools forthe study of Traumatic Brain Injuries (TBIs) but lack significantanatomical details for the investigation of morphology or age-dependantinjury mechanisms. In this context, the use of deformable registrationalgorithms for the generation of personalized head models is veryconsistent for the development of improved protection systems likehelmets. This thesis presents the performances of the registrationpipeline Demons combined to the Difformable Registration via AttributesMatching and Mutual-SaliencyWeighting (DRAMMS) for the generationof FE head models. Twelve subject-specific models are formed bymorphing the baseline mesh with the displacement fields resultingfrom the registration methods. The obtained models are assessedand compared through the evaluation of elements’ quality by analysisof the distortion index distribution. The Dice similarity coefficientis also calculated to estimate the personalization accuracy of theapplied pipeline. The Demons+DRAMMS registration pipeline showssatisfactory personalization accuracy for cranial mask and internalbrain structures. No significant degradation of mesh quality dueto the morphing process or specific subject morphology is observed.The present work corroborates previous study regarding the use ofDemons+DRAMMS registration pipeline for generating subject-specifichead models and validates the performances of the registration methodsand the repeatability of the morphing process for this purpose.