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50: Image Processing for Volume Graphics
Tuesday, Full Day
8:30 am – 5:15 pm
Room 007CD
This course explores the essential tools and techniques
for processing volume data as part of rendering and visualization.
It examines several aspects in depth: mathematical foundations
of volume image processing, transfer function management,
wavelets, shape modeling, and level-set techniques. Attendees
are invited to bring their questions about their most
difficult volume datasets.
Prerequisites
Basic knowledge of 3D computer graphics and an understanding
of the basic principles of image processing.
Topics
The mathematics of the elements of effective volume visualizations
and the processes by which they are created. Emerging
topics in volume-data processing including level sets,
shape extraction using adaptive implicit systems, and
model-based segmentation.
Organizer
Terry S. Yoo
National Institutes of Health
Lecturers
Guido Gerig
University of North Carolina at Chapel Hill
Gordon Kindlmann
Ross Whitaker
University of Utah
Raghu Machiraju
The Ohio State University
Torsten Möller
Simon Fraser University
Terry S. Yoo
National Institutes of Health
| Module
1 – Foundations of Filtering |
| 8:30 |
Welcome
and Overview
Yoo |
| 8:40 |
Filtering
and Frequency Fundamentals
Yoo |
| 9:00 |
Sampling,
Interpolation, and Filter Design
Moller |
| 10:15 |
Break |
| Module
2 – Transfer Functions and Feature Detection |
| 10:30 |
Transfer
Function: Design and Management
Kindlmann |
| 11:45 |
Feature
Extraction
Machirju |
| 12:15 |
Lunch |
| Module
3 – Wavelets and Shape Models |
| 1:30 |
Wavelets
for Graphics and Visualization
Machiraju |
| 2:15 |
Model
Based Segmentation
Gerig |
| 3:15 |
Break |
| Module
4 – Deformable Implicit Surfaces and Level
Sets |
| 3:30 |
Deformable
Implicit Surfaces
Yoo |
| 4:00 |
Level
Sets
Whitaker |
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