Deep learning-aided segmentation combined with finite element analysis reveals a more natural biomechanic of dinosaur fossil.

ABSTRACT: Finite element analysis (FEA), a biomechanical simulation technique capable of providing direct mechanical visualization for CT-based digital models, has been extensively applied to fossil image datasets to address key evolutionary questions in paleontology. However, the rock matrix filling intertrabecular space of fossils often causes severe deviations in FEA results. Segmentation strategies such as thresholding and manual labeling have been employed to mitigate these disturbances. However, the efficiency of manual segmentation and the accuracy of thresholding remain questionable. In this study, we applied FEA combined with deep learning-based segregation on a femoral specimen of Jeholosaurus (a small bipedal dinosaur). This novel methodology efficiently generates the FE model with stress

SUBMITTER: Zhang L 

PROVIDER: S-EPMC12015504 | biostudies-literature | 2025 Apr

REPOSITORIES: biostudies-literature