Integrating finite element analysis and physics-informed neural networks for biomechanical modeling of the human lumbar spine.

Journal: North American Spine Society journal
Published Date: Feb 17, 2025

Abstract

BACKGROUND: Comprehending the biomechanical characteristics of the human lumbar spine is crucial for managing and preventing spinal disorders. Precise material properties derived from patient-specific CT scans are essential for simulations to accurately mimic real-life scenarios, which is invaluable in creating effective surgical plans. The integration of Finite Element Analysis (FEA) with Physics-Informed Neural Networks (PINNs) offers significant clinical benefits by automating lumbar spine segmentation and meshing.

Authors

  • Mohsen Ahmadi
    Department of Electrical Engineering and Computer Science, Florida Atlantic University, Boca Raton, FL, United States.
  • Debojit Biswas
    Department of Biomedical Engineering, Florida Atlantic University, Boca Raton, FL, United States.
  • Rudy Paul
    Department of Ocean and Mechanical Engineering, Florida Atlantic University, Boca Raton, FL, United States.
  • Maohua Lin
  • Yufei Tang
  • Talha S Cheema
    Department of Neurosurgery, Marcus Neuroscience Institute, Boca Raton Regional Hospital, Boca Raton, FL, United States.
  • Erik D Engeberg
    Florida Atlantic University, Ocean and Mechanical Engineering Department, 777 Glades Road; Bldg. 36, Room 190, Boca Raton, FL 33431, USA. The University of Akron, Mechanical Engineering Department, ASEC, Room 101, Akron, OH 44325-3903, USA.
  • Javad Hashemi
    Department of Biomedical Engineering, Florida Atlantic University, Boca Raton, FL, United States.
  • Frank D Vrionis
    Department of Neurosurgery, Marcus Neuroscience Institute, Boca Raton Regional Hospital, Boca Raton, FL, United States.

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