Towards a radiation free numerical modelling framework to predict spring assisted correction of scaphocephaly-Reference-Cited by-同舟云学术

Towards a radiation free numerical modelling framework to predict spring assisted correction of scaphocephaly

Published:2023-12-18 Issue: Volume: Page:1-10
ISSN:1025-5842
Container-title:Computer Methods in Biomechanics and Biomedical Engineering
language:en
Short-container-title:Computer Methods in Biomechanics and Biomedical Engineering

Author:

Garate Andikoetxea Begona¹,Ajami Sara¹²,Rodriguez-Florez Naiara³⁴,Jeelani N. U. Owase²,Dunaway David²,Schievano Silvia¹²,Borghi Alessandro¹²⁵

Affiliation:

1. University College London, United Kingdom

2. Great Ormond Street Hospital, London, United Kingdom

3. Universidad de Navarra, Spain

4. Ikerbasque, Spain

5. Department of Engineering, Durham University, Durham, United Kingdom

Funder

NIHR Great Ormond Street Hospital Biomedical Research Centre

Great Ormond Street Hospital for Children Charity

NIHR British Research Council Advanced Therapies for Structural Malformations and Tissue Damage pump-prime

Great Ormond Street Hospital Charity Clinical Research Starter

European Research Council

Publisher

Informa UK Limited

Subject

Computer Science Applications,Human-Computer Interaction,Biomedical Engineering,General Medicine,Bioengineering

Link

https://www.tandfonline.com/doi/pdf/10.1080/10255842.2023.2294262

Reference42 articles.

1. Three-Dimensional Stereophotogrammetry in the Evaluation of Craniosynostosis: Current and Potential Use Cases

2. Surgical Treatment of Nonsyndromic Unicoronal Craniosynostosis

3. A population-specific material model for sagittal craniosynostosis to predict surgical shape outcomes

4. Borghi A, Rodriguez-Florez N, Jeelani O, Dunaway D, Schievano S. 2018. Population-derived material properties for Craniosynostosis patients improve outcome predictions in Craniofacial Surgery. In: Proceedings of the 8th World Congress of Biomechanics.

5. Spring assisted cranioplasty: A patient specific computational model