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Subject-Specific Head Model Generation by Mesh Morphing: A Personalization Framework and Its Applications
KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Neuronic Engineering.ORCID iD: 0000-0001-8522-4705
2021 (English)In: Frontiers in Bioengineering and Biotechnology, E-ISSN 2296-4185, Vol. 9, article id 706566Article in journal (Refereed) Published
Abstract [en]

Finite element (FE) head models have become powerful tools in many fields within neuroscience, especially for studying the biomechanics of traumatic brain injury (TBI). Subject-specific head models accounting for geometric variations among subjects are needed for more reliable predictions. However, the generation of such models suitable for studying TBIs remains a significant challenge and has been a bottleneck hindering personalized simulations. This study presents a personalization framework for generating subject-specific models across the lifespan and for pathological brains with significant anatomical changes by morphing a baseline model. The framework consists of hierarchical multiple feature and multimodality imaging registrations, mesh morphing, and mesh grouping, which is shown to be efficient with a heterogeneous dataset including a newborn, 1-year-old (1Y), 2Y, adult, 92Y, and a hydrocephalus brain. The generated models of the six subjects show competitive personalization accuracy, demonstrating the capacity of the framework for generating subject-specific models with significant anatomical differences. The family of the generated head models allows studying age-dependent and groupwise brain injury mechanisms. The framework for efficient generation of subject-specific FE head models helps to facilitate personalized simulations in many fields of neuroscience.

Place, publisher, year, edition, pages
Frontiers Media SA , 2021. Vol. 9, article id 706566
Keywords [en]
finite element modeling, personalized simulation, traumatic brain injury, brain stimulation, neuroimage registration, biomechanics
National Category
Other Medical Engineering Vehicle Engineering
Identifiers
URN: urn:nbn:se:kth:diva-305094DOI: 10.3389/fbioe.2021.706566ISI: 000715320300001PubMedID: 34733827Scopus ID: 2-s2.0-85118358382OAI: oai:DiVA.org:kth-305094DiVA, id: diva2:1613611
Note

QC 20211123

Available from: 2021-11-23 Created: 2021-11-23 Last updated: 2022-06-25Bibliographically approved

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Li, Xiaogai

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CiteExportLink to record
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Citation style
  • apa
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  • modern-language-association-8th-edition
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  • Other style
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  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
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More languages
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  • html
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  • asciidoc
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