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|a HCDD
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|a Computational biomechanics for medicine :
|b personalisation, validation and therapy /
|c Martyn P. Nash, Poul M.F. Nielsen, Adam Wittek, Karol Miller, Grand R. Joldes, editors.
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|a Cham, Switzerland :
|b Springer,
|c [2020]
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|a 1 online resource (viii, 149 pages) :
|b illustrations
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|a text
|b txt
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|a online resource
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|b PDF
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|a Includes bibliographical references and index.
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|a Intro; Preface; Contents; Biomechanical Simulation of Vaginal Childbirth: The Colors of the Pelvic Floor Muscles; 1 Introduction; 2 Mechanism of Normal Labor; 3 Biomechanical Childbirth Simulation; 3.1 Constitutive Models; 3.1.1 Isotropic Constitutive Models: Simulating the Passive Behavior; 3.1.2 Anisotropic Constitutive Models: Simulating the Passive and Active Behavior of the Muscle; 3.2 In Vivo Characterization; 3.3 Vaginal Delivery Simulation; 4 Personalized Childbirth Models; 5 Conclusions; References
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|a Patient-Specific Modeling of Pelvic System from MRI for Numerical Simulation: Validation Using a Physical Model1 Introduction; 2 Materials and Methods; 2.1 Initial Generic CAD Model; 2.2 Physical Model; 2.3 Geometry Reconstruction from Image Data; 2.4 Reduced CAD Model and Geometrical Morphing; 3 Results; 3.1 Comparison Between Manual Procedure and Initial CAD Model; 3.2 Comparison Between Computer-Assisted Reconstruction and Initial CAD Model; 4 Discussions; 5 Conclusion; References; Numerical Analysis of the Risk of Pelvis Injuries Under Multidirectional Impact Load; 1 Introduction
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|a 2 Methodology2.1 Boundary Condition; 3 Results and Discussion; 4 Conclusions; References; Parametric Study of Lumbar Belts in the Case of Low Back Pain: Effect of Patients' Specific Characteristics; 1 Introduction; 2 Methodology; 2.1 Trunk Modelling; 2.1.1 Construction of Geometric Model; 2.1.2 Finite Element Modelling of the Trunk; 2.1.3 Modelling of the Lumbar Belt; 2.1.4 Assessment of Belt Modelling; 2.2 Parametric Study; 2.2.1 Input Parameters; 2.2.2 Output Parameters; 2.2.3 Design of Experiments; 3 Results; 3.1 Convergence Study; 3.2 Assessment of Belt Modelling
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|a 3.3 Example of Detailed Results for a Modelled Subject3.4 Parametric Study; 4 Discussion; 4.1 Trunk Model; 4.2 Mechanism of Action of a Lumbar Belt; 5 Conclusion; References; Quantitative Validation of MRI-Based Motion Estimation for Brain Impact Biomechanics; 1 Introduction; 2 Materials and Methods; 2.1 Experimental Phantom; 2.2 Image Acquisition and Motion Estimation; 3 Results and Discussion; 3.1 Displacement Calibration; 3.2 Strain Calibration; 4 Conclusion; References; Meshless Method for Simulation of Needle Insertion into Soft Tissues: Preliminary Results; 1 Introduction; 2 Methods
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|a 2.1 Meshless Method for Simulation of Needle Insertion into Soft Tissues2.1.1 Meshless Total Lagrangian Explicit Dynamics (MTLED) Algorithm for Computing Soft Tissue Deformations; 2.1.2 A New Method for Modelling of Interactions Between the Needle and Soft Tissues Using Kinematic Approach; 2.2 Verification of the Proposed Meshless Method for Simulation of Needle Insertion into Soft Tissues; 2.2.1 Determining the Parameters for Our Meshless Method for Simulation of Needle Insertion into Soft Tissues
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|a 2.3 Determining the Parameters for New Algorithm for Modelling of Interactions Between the Needle and Soft Tissues Using Kinematic Approach
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|a This book contains contributions from computational biomechanics specialists who present and exchange opinions on the opportunities for applying their techniques to computer-integrated medicine, including computer-aided surgery and diagnostic systems. Computational Biomechanics for Medicine collects peer-reviewed chapters from the annual Computational Biomechanics for Medicine Workshop, in conjunction with the Medical Image Computing and Computer Assisted Intervention [MICCAI] Society conference. The works are dedicated to research in the field of methods and applications of computational biomechanics to medical image analysis, image-guided surgery, surgical simulation, surgical intervention planning, disease diagnosis and prognosis, analysis of injury mechanisms, implant and prosthesis design, artificial organ design, and medical robotics. These chapters will appeal to a wide range of researchers and students within the fields of engineering and medicine, as well as those working in computational science.
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|a Medicine
|x Data processing.
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|a Biomedical engineering
|x Data processing.
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|a Radiology.
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|a Mechanics.
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|a Robotics.
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|a Automation.
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|a biomedical engineering.
|2 aat
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|a radiology.
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|a mechanics (physics)
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|a automation.
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|a Biomedical engineering
|x Data processing
|2 fast
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|a Medicine
|x Data processing
|2 fast
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|a proceedings (reports)
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|a Conference papers and proceedings
|2 fast
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|a Conference papers and proceedings.
|2 lcgft
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|a Actes de congrès.
|2 rvmgf
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| 700 |
1 |
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|a Nash, Martyn P.,
|e editor.
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| 700 |
1 |
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|a Nielsen, Poul M. F.
|q (Poul Michael Fønss),
|e editor.
|1 https://id.oclc.org/worldcat/entity/E39PCjw4mmkqm8Q4HTbk7k3gBq
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| 700 |
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|a Wittek, Adam,
|e editor.
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| 700 |
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|a Miller, Karol,
|e editor.
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| 700 |
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|a Joldes, Grand R.,
|e editor.
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| 776 |
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|i Print version:
|a Nash, Martyn P.
|t Computational Biomechanics for Medicine : Personalisation, Validation and Therapy.
|d Cham : Springer, ©2019
|z 9783030159221
|
| 856 |
4 |
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|u https://holycross.idm.oclc.org/login?auth=cas&url=https://link.springer.com/10.1007/978-3-030-15923-8
|y Click for online access
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|a SPRING-ENGINE2020
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|a 92
|b HCD
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