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Scientific Training III - Statistical Shape Modelling and Simulation of Deformable Models for Biomechanics
Second title: Statistical Shape Modelling and Simulation of Deformable Models for Biomechanics
Provider: Faculty of Science

Activity no.: 5175-19-02-32 
Enrollment deadline: 26/06/2019
Date and time01.07.2019, at: 09:00 - 05.07.2019, at: 17:00
[antalgange]5
Regular seats30
ECTS credits3.00
Contact personAnnette Lange    E-mail address: alange@di.ku.dk
Enrolment Handling/Course OrganiserKenny Erleben    E-mail address: kenny@di.ku.dk
Written languageEnglish
Teaching languageEnglish
Exam requirementsTBA
Exam formAndet/Other
Exam detailsTBA
Grading scaleCompleted/ Not completed

Aim and content
Course content

Simulation is a valuable tool when working with biomechanical modeling of humans as it allows for analysis or prediction for either scenarios that would be too invasive or high risk to conduct on real human experiments or to fill in the gaps where only sparse knowledge or data is accessible. On the other hand data-driven approaches and statistical analysis of larger populations have similar shown to be extremely powerful in understanding the nature of how things work or more precisely how the sensitivity of different factors influence each other. The two approaches: simulation and statistical analysis are not necessarily disjoint given one is model driven and the other data-driven. In this course we peel of the first layer in combining these two approaches in the context of biomechanical modeling of humans.

In this course we will focus on how to bridge the gap between data and simulation of deformable models. The courses addresses fundamental background and terminology in simulation of deformable models with multiple practical examples. Participants will learn to use state of the art simulation tools such as FEniCs, Sofa and possible other tools as well. Having formed a strong basis for continuum mechanics and simulations the course tries to connect simulation as a tool to statistical analysis. How can we use data for analysis and how can simulation results be processed by analysis to conclude hypotheses on larger populations.

Formel requirements
The course aims at combining basic knowledge and skills in two different disciplines into one common frame. The intended audience is PhDs in computer science who does not necessarily have a strong background in both these fields.

Learning outcome
Learning objectives:

i) Describe shapes, shape spaces, and shape variability in the context of template shapes deformed by the action of deformations of the shape domain.

ii) Perform statistical analysis and computations on simple shape spaces.

iii) Apply statistical analysis to large scale simulation studies

iv) Account for common challenges in biomechanical modeling, describe how to cope without a gold standard, validation and verification.

v) Derive basic definitions of stress and strain tensors and apply these to compute stress/strain measures given known displacement fields

vi) Describe what plasticity, viscosity, yield point, yield strength, tensile limit etc and identify these concepts correctly if given for instance a stress-strain curve

vii) Explain the governing equations of motion for hyper elastic material simulation and run simulations using different constitutive equations in for instance FEniCS or FEBio

viii) Present visualizations of simulation results such as von Misses or Tresca stress or similar and reason about the meaning of high and low values (yield values)

ix) Describe how to use multi-model simulation with contact in SOFA

x) Setup and run a simple SOFA simulation with deformable and rigid bodies in contact.

Literature
TBA

Target group

The course aims at combining basic knowledge and skills in two different disciplines into one common frame. The intended audience is PhDs in computer science who does not necessarily have a strong background in both these fields.

Lecturers

Jack Hale is a Research Scientist in the Department of Computational Engineering Sciences at the University of Luxembourg. His work focuses on understanding uncertainty in physical systems modelled by partial differential equations. He sits on the steering council of the FEniCS Project, an open source computing platform for solving partial differential equations using the finite element method.

Lars Beex is a Research Scientist at the University of Luxembourg who has received the Biezeno Solid Mechanics Award 2012 for his PhD thesis. He has co-authored 20+ publications related to the computational modelling of solids, of which 10+ as first author. His work focuses on mechanical phenomena are geometrical nonlinearities, plasticity, damage, contact and stochastic input fields. He aims to incorporate these phenomena in multiscale approaches, such as the quasicontinuum method, and model-order-reduction frameworks in order to increase computational efficiency.

Dr. Hugo Talbot originally studied mechanical engineering, and graduated in 2010 from both Karlsruhe Institute of Technology (Germany) and INSA Lyon (France). He defended his PhD in medical simulation at Inria (France) in July 2014. His work focused on the real-time simulation of the electrical activity of the human heart. From 2014 until late 2015, Hugo worked on the simulation of cryoablation and cardiac electrophysiology as research engineer.
Since January 2016, Hugo Talbot is the coordinator of the open-source project SOFA. SOFA is an open-source framework for multi-physics simulation and is being developed for more than 12 years. Today, SOFA benefits from a large international community made up of research centers and companies. The objectives of Hugo are to develop the community, to ensure the technical evolution of the software, to foster research collaborations and technology transfers.

Stefan Sommer received his M.Sc. in mathematics in 2008 and his PhD in computer science in 2012 from the University of Copenhagen. He is currently an associate professor at the Department of Computer Science, University of Copenhagen. His research interests focus on modelling and analysis of data with complex structure, including nonlinear statistics, image analysis, shape modelling, and applied aspects of stochastic analysis in nonlinear geometries.

 

Sune Darkner is associate professor at KU since 2012. His main research topic is medical image. He work mainly on neuro-imaging data such as MRI and PET and holds expertise on image registration and the statistics on shapes and deformations in relation to simulation of soft tissue. He has published more than 40 journal and conference papers, has co-organized workshops under MICCAI and is co-supervising 1 PhD, 2 others finished primo 2015. He is member of RAINBOW's Supervisor Board and supervisor of ESR 2 and ESR 4. 

 

John Rasmussen is a professor of biomechanics at Aalborg University. His research is centered on biomechanics, biomedical engineering and sports engineering. In the late 1990’ies, he formed the AnyBody Research Project at Aalborg University, which he is still heading. One of the aims of the project is to develop methods for analysing the biomechanics of the human body involving bones, joints, muscles and tendons. This research contributes to the treatment of osteoarthritis, general disability and to optimization of sports performances. In addition to his academic work, John Rasmussen is involved in the private sector as chief executive officer at AnyBody Technology A/S from 2001 to 2008 and subsequently the CTO of the same company.He is member of RAINBOW's Supervisor Board and supervisor of ESR 5.


Content

Please see programme (will be updated ongoingly) https://rainbow.ku.dk/training/scientific-training-iii/

 

Payment  of 490 Euro

Please go to the payment site via this address:

https://science.easysignup.com/100/

 


Course dates and venue1 - 5 July 2019

Venue:
Copenhagen Navy Association at Nyholm
Takkeladsvej opgang 3
1439 Copenhagen K

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