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Geometric Modeling

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Title: Geometric Modeling


1
Biomedical Computing Collaboration Challenges
Chris Johnson Scientific Computing and Imaging
Institute University of Utah www.sci.utah.edu
2
Biomedical Imaging and Modeling
3
Biomedical Simulation
4
Biomedical Visualization
5
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6
A Biology/Bioengineering Grand Challenge
Modeling, Simulation, Visualization, Software
Frameworks, Databases, Networking, Grids
Courtesy Peter Hunter, University of Auckland
7
Bioengineering Example
8
Software SCIRun, BioPSE, PowerApps
  • Computational Workbench
  • Image Processing, Modeling, Simulation,
    Visualization Tools
  • Layered Software System
  • Dataflow/Modules
  • PowerApps
  • Interactive Problem Set up and Computing
  • What if..? Problem Exploration
  • Flexible, Extensible Environment
  • Open Source Software (MIT Public License)
  • Module Development Tool and Bridging
  • PowerApps (BioFEM, BioTensor, BioImage)
  • Irix, Linux, Mac OSX, Windows

9
SCIRun/BioPSE Extensibility
  • Leverage existing utilities/programs
  • Extensibility through bridges

VisTrails
Matlab
NetSolve
SQL
lib
socket
BioPSE
PETSc
lib
ITK
lib
10
Cardiac Electrical Wave Propagation
Structural and chemical information
Cellular model of electrical conductivity/ action
potential propagation
Bidomain model of an ischemic heart
11
Software Tool Integration
Computational Cardiology Software Integration
Example
Matlab for cellular modeling and some numerics
Matlab tools
CardioWave is specially designed to run on a
cluster to compute bidomain simulations
CardioWave Simulation tool
SCIRun visualization
SCIRun for visualization, imaging, integration
12
SCIRun
gt Data flow paradigm gt Integrating
different programs together gt Advanced
visualization
13
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14
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15
HealthGrid, BIRN, Lariat, NCBCs, INBRE
16
Guiding Principles
  • Driven By Needs of Users
  • Accessibility and Usability
  • Integration and Extensibility
  • Performance and Control
  • Software Engineering
  • Open Source Open Data Open Science
  • Verification and Validation

17
Software Engineering
Software Engineering is Often Overlooked! Software
Engineering is Hard! Software Engineering is
Important!
18
The Gap
Biomedical Sciences
CS, Math, CSE
Biomedical Computing
Biomedical Sciences
CS, Math, CSE
19
Information Big Bang
20
NIH/NSF Visualization Research Challenges Report
http//tab.computer.org/vgtc
21
PITAC Reports www.nitrd.gov
22
More Information
  • www.sci.utah.edu
  • crj_at_sci.utah.edu

23
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24
IEEE Computer Graphics and Applications,
July/August, 2004 www.sci.utah.edu
25
Top Visualization Research Issues
  • Think About the Science
  • Quantify Effectiveness
  • Error and Uncertainty Visual Representation
  • Perceptual Issues
  • Novel Hardware Architectures
  • HCI
  • Global/Local Visualization
  • Time Dependent Visualization
  • Integrated PSEs
  • Multi-field Visualization
  • Integrating Info and Sci Visualization
  • Interesting Feature Detection
  • Scalable, Distributed and Grid-Base Visualization
  • Theory of Visualization

IEEE Computer Graphics and Applications,
July/August 2004
26
Grid Visualization Algorithms
  • Compression (wavelets, multiresolution, mpeg,
    etc.)
  • Importance Based Rendering
  • View Dependent
  • Image Based Rendering
  • Adaptive (Resource Aware) Parallel/Distributed
    Techniques

27
Volume Rendering
Maximum Intensity Projection (MIP)
Full Volume Rendering
28
Volume Rendering
enamel / background
dentin / pulp
dentin / background
dentin / enamel
1D not possible 2D specificity not as good
29
Visualization Software BioImage
30
Time Dependent Visualization
Time-dependent BioImage volume rendering of a 4D
CT dataset. Interaction rate on a PC running
Linux is approximately 10 frames per second.
Data from collaborator George Chen (MGH).
31
VisTrails History Management
A single VisTrail is a complete collection of
dataflows!
32
VisTrails Multi-View Functionality
33
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34
ITK An Interactive Segmentation Tool
www.itk.org
35
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36
Large-Scale Images
Images courtesy of Mark Ellisman, UCSD
37
Large-Scale Imaging/Visualization
Image courtesy of Art Toga, UCLA
38
New Visualization Techniques
39
Visualization Algorithm Scalability
Speedup for k n0.8
104
NOISE
103
Speedup
102
Visible Woman CT Dataset 1Gb MC - 280s
4.5m PISA - .17s Mac G5, 2Ghz
101
100
107
108
109
1010
1011
106
Volume Size
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