ArticleAnnals of biomedical engineering2020
An Image Registration-Based Morphing Technique for Generating Subject-Specific Brain Finite Element Models.
Article in Annals of biomedical engineering, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed, 41 citations in OpenAlex.
- Mechanical deformation explains distinct neuroimaging patterns and etiologies in brain trauma.NeuroImage · 2026Article
- Multimodal characterization of intracranial biomechanics in a 3D biofidelic head surrogate.Journal of the mechanical behavior of biomedical materials · 2026Article
- Average Responses of Brain Displacement Under Rotational Loading for Computational Model Validation.IEEE transactions on bio-medical engineering · 2025Article
- Average Biomechanical Responses of the Human Brain Grouped by Age and Sex.Annals of biomedical engineering · 2025Article
- Surface-based versus voxel-based finite element head models: comparative analyses of strain responses.Biomechanics and modeling in mechanobiology · 2025Article
- A fast-modeling framework for personalized human body models based on a single image.Medical & biological engineering & computing · 2025Article
- A Spatial Interpolation Approach to Assign Magnetic Resonance Imaging-Derived Material Properties for Finite Element Models of Adeno-Associated Virus Infusion Into a Recurrent Brain Tumor.Journal of biomechanical engineering · 2024Article
- Personalization of human body models and beyond via image registration.Frontiers in bioengineering and biotechnology · 2023Article
- Use of Brain Biomechanical Models for Monitoring Impact Exposure in Contact Sports.Annals of biomedical engineering · 2022Review
- Quantifying the Effect of Sex and Neuroanatomical Biomechanical Features on Brain Deformation Response in Finite Element Brain Models.Annals of biomedical engineering · 2022Article
- Concussion Prone Scenarios: A Multi-Dimensional Exploration in Impact Directions, Brain Morphology, and Network Architectures Using Computational Models.Annals of biomedical engineering · 2022Article
- Cumulative strain-based metrics for predicting subconcussive head impact exposure-related imaging changes in a cohort of American youth football players.Journal of neurosurgery. Pediatrics · 2022Article
- Brain architecture-based vulnerability to traumatic injury.Frontiers in bioengineering and biotechnology · 2022Article
- Integrating material properties from magnetic resonance elastography into subject-specific computational models for the human brain.Brain multiphysics · 2021Article
- Subject-Specific Head Model Generation by Mesh Morphing: A Personalization Framework and Its Applications.Frontiers in bioengineering and biotechnology · 2021Article
- Calibration of a Heterogeneous Brain Model Using a Subject-Specific Inverse Finite Element Approach.Frontiers in bioengineering and biotechnology · 2021Article
Corrections and comments
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Authors and funding
8 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Finite element (FE) models of the brain are crucial for investigating the mechanisms of traumatic brain injury (TBI). However, FE brain models are often limited to a single neuroanatomy because the manual development of subject-specific models is time consuming. The objective of this study was to develop a pipeline to automatically generate subject-specific FE brain models using previously developed nonlinear image registration techniques, preserving both external and internal neuroanatomical characteristics. To verify the morphing-induced mesh distortions did not influence the brain deformation response, strain distributions predicted using the morphed model were compared to those from manually created voxel models of the same subject. Morphed and voxel models were generated for 44 subjects ranging in age, and simulated using head kinematics from a football concussion case. For each subject, brain strain distributions predicted by each model type were consistent, and differences in strain prediction was less than 4% between model type. This automated technique, taking approximately 2 h to generate a subject-specific model, will facilitate interdisciplinary research between the biomechanics and neuroimaging fields and could enable future use of biomechanical models in the clinical setting as a tool for improving diagnosis.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.