IBBM 18

 Program

General Course Objectives

The goal of this program is to develop a basic set of skills and practical experience in the area of image-based modeling and simulation as it applies to bioelectricity and biomechanics. The resulting 10-day course builds on existing knowledge in mathematics and physics and leverages field-specific expertise and hands-on experience to explore problems in bioelectricity and biomechanics that arise in current biomedical research and clinical practice.

With a strong emphasis on practical use cases, this course provides participants with training in the numerical methods, image analysis, and computational tools necessary to carry out end-to-end, image based, subject-specific simulations in bioelectricity or biomechanics, using freely available software.

This course expands on short (1-3 day) courses offered over the past 15 years by the Center for Integrated Biomedical Computing (CIBC) and Musculoskeletal Research Laboratories (MRL) in the Scientific Computing and Imaging (SCI Institute) at the University of Utah.

We particularly invite participation from students in health-related sciences belonging to underrepresented groups as defined by the NIH (find out more on the NIH Website ).

Course Format

The course curriculum will include 10 days of a combination of lectures, demos, and structured laboratory exercises as well as mentored but unstructured lab time for pursuing individual research projects. We will provide sample project topics but also encourage participants to bring their own research ideas, topics, and data. The program will begin with a block of common curriculum and then run in parallel streams for bioelectricity and biomechanics. See schedule, below, for more details.

The program will also include keynote lectures from leaders in the field of computational biomedical engineering and practical mentoring sessions from highly experienced and successful researchers on topics such as proposal writing and the responsible conduct of research. The congenial setting away from urban centers and in the beauty of the Wasatch Mountains will provide easy opportunities for outdoor activities and unstructured time for professional interactions.

Modules

  • Image Processing
  • Geometry Processing
  • Numerical Methods
  • Visualization
  • Computational Bioelectric Fields or Computational Biomechanics:

Computational Bioelectric Fields and Computational Biomechanics are two modules offered in parallel tracks over the last three days of the course. Students will choose to take one or the other.

Agenda

This is an outline only. This year's agenda will be shared with participants.

IBBM Reception @ Utah Olympic Park in Park City, Utah. 

 

Week 1 Sunday
Monday
Tuesday
Wednesday
Thursday
Friday
Saturday  
Morning Arrivals Intro and Welcome Image Processing
and
Segmentation
Scientific Visualization
Geometry
Processing
Numerical
Methods
Numerical
Methods
 

 
Image Processing
and 
Segmentation
 
 
Lunch Keynote Leo Grady            
Afternoon Image Processing
and
Segmentation
Image Processing
and
Segmentation
Geometry
Processing
Geometry
Processing
SCI Institute / SMBB Numerical
Methods 
 

 

Grant Strategy 

 

 Social
   
Responsible Conduct of Research  
Evening Welcome Reception         
 
   
   
Week 2 Sunday
Monday
Tuesday
Wednesday
Thursday
Friday
 
Morning Biking/
Hiking/
Outdoor

Activities
Geometry
Processing
Bioelectric
Activity
and
Fields
Bio-
mechanics
Bioelectric
Activity
and
Fields
Bio-
mechanics
Bioelectric
Activity and
Fields
Bio-
mechanics
  Departures






Lunch   Keynote Silvia Salinas Blemker  Keynote Steven Schiff Keynote Gerard Ateshian
 
Afternoon Bioelectric
Activity 
and
Fields
Bio-
mechanics
Bioelectric
Activity
and
Fields
Bio-
mechanics
Bioelectric
Activity
and
Fields
Bio-
mechanics
Project








Evening Final Reception  






Description of Modules

Image Processing and Segmentation (Lecture and Labs)
The Image Processing Module presents a concentrated introduction to the basic concepts of low-level image processing. This is the first step in a pipeline that forms the workflow for many examples of patient-specific biophysical simulation and relies on the processing of 3D images, typically CT and MRI, prior to the construction of geometric models. This module will introduce students to terminology, mathematical frameworks for images, basic algorithms, and hands-on experience with software tools. Upon completion, participants will have the experience to use off-the-shelf tools, the background knowledge to learn more depth and detail independently, and the vocabulary needed to collaborate effectively with specialists in image processing.

Geometry Processing and Meshing (Lecture and Labs)
The image based modeling pipeline emphasizes body-fitting meshes for patient anatomy and finite element methods for biophysical simulation. One of the main challenges of this type of processing and analysis, and one of the main impediments to its widespread use, is the construction of meshes that conform to patient geometry/anatomy. The goal of this module is to introduce the terminology and concepts associated with tessellations of biomedical objects. Upon completion, participants will have both a broad background in the topic and a more focused exposure to body-fitting tetrahedral meshes and their association with segmentations of 3D images, along with experience with available open-source software tools for mesh generation.

Numerical Methods: Finite Elements and Simulation (Lecture and Labs)
Simulation in biomedicine is often based on the application of the finite element method (FEM), a numerical approximation technique for solving both linear and nonlinear partial differential equations that capture biological behavior. The goal of this module will be to explain the application of the finite element method to solving problems in electrophysiology or biomechanics. The course assumes some familiarity with this topic and will review and then build on that knowledge to prepare participants for subsequent use in example problems. Upon completion, participants will understand how to apply this numerical approach and anticipate some of the associated computational requirements and challenges.

Scientific Visualization (Lecture and Labs)
Scientific visualization is the use of computer graphics to create images that convey salient information about underlying scientific data and processes. This is an essential capability at all stages of the image based modeling pipeline and there is an associated range of specific techniques and software used in the field. The goal of this module is to provide basic knowledge of the computer graphics techniques employed in scientific visualization, e.g., volume rendering, surface based rendering of scalar and vector quantities, tensor visualization, and color mapping. Upon completion, participants will be able to use a set of these of techniques, implemented in open source software tools, to interpret data at all stages of the modeling pipeline.

Computational Bioelectricity* (Lecture and Labs)
The study of modeling and simulation of bioelectric fields is one of the two main thrusts of this curriculum. The goals of this module are to provide intermediate-level knowledge of the biophysical basis of bioelectricity, to develop a broad understanding of a range of physical and mathematical models to describe both sources of bioelectricity and the media in which they propagate, and to acquire a working, practical knowledge of the computational tools that implement these models. Informed by practical applications of this knowledge, by the end of the course students will be equipped to evaluate bioelectric field problems in their own interest domains, identify and understand various approaches for capturing the behavior of interest, and then implement these ideas in ways that will allow comparison with measurements or other forms of validation.

Computational Biomechanics* (Lecture and Labs)
The purpose of this module is to review the background necessary for students to pursue subject-specific modeling in computational biomechanics, and to present the most important practical information related to model construction and analysis with nonlinear finite element methods. The module consists of a didactic portion (lectures), hands-on demonstrations using the open-source finite element code FEBio, and the solving of sample problems. The didactic portion of the module introduces the basic terminology of computational biomechanics and reviews the fundamental concepts and field equations of continuum mechanics. This portion includes a review of finite deformation kinematics, common constitutive models for biological materials and biomaterials, and boundary conditions that are typically encountered in computational biomechanics. Upon completion, participants will be able to identify and execute the appropriate mathematical, numerical, and computation approaches for a range of realistic problems in the domain of biomechanics.

*Computational Bioelectricity and Computational Biomechanics are two modules offered in parallel tracks over the last three days of the course. Students will choose to take one or the other. 
 
 
Prerequisites
Our experience with current users and educational programs in bioengineering and biomechanics provides the following set of expectations and prerequisites for maximal benefit from the proposed course:
  • Linear algebra at the intermediate level.
  • Vector calculus at the level required to solve problems in classical physics (motion and/or electrostatics).
  • Differential equations, including ODEs and some PDEs.
  • Basic statistics.
  • Knowledge of sophomore level physics, including electrostatics.
  • Knowledge of solid mechanics, strength of materials, or continuum mechanics (for students in computational biomechanics).
Participants will carry out computation exercises throughout the course and should bring their own laptop computers. Additional laptop computers will be available for use in the course but please contact us beforehand to arrange for access to such a loaner. We encourage participants to download this software before arriving at the workshop and we can can provide any necessary assistance either remotely or at the start of the course.

Recommended background reading will be listed in the modules.