PhD in Computing

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42024 - Advanced Scientific Visualization (VRA)

Type: Elective
Semester: S3
ECTS: 5
Teaching Points: 12
Offer: Annual
Responsible Unit: LSI
Responsible: Imma Boada, Miquel Feixas
Language: English
Requirements:


GOALS
This course will provide an introduction to basic and advanced topics of processing and visualization of both scalar and tensor datasets. Special emphasis will be placed on the application of information theory to all these techniques.
Data processing topics will include segmentation and registration techniques.
Multiresolution and data compression strategies will be also studied. Main visualization techniques will be reviewed and also their application to multimodal rendering.

CONTENTS
1. The visualization pipeline.
  • Fundamentals of image preprocessing and acquisition techniques.
  • Data representation.
  • Multiresolution and hierarchical representations.
2. Basic visualization algorithms
  • Visualization of scalar fields.
  • Indirect volume rendering
  • Direct Volume Rendering
3. Data compression techniques.
  • Basic concepts of information theory.
  • Coding theory.
  • Lossless data compression.
  • Lossy compression techniques.
4. Segmentation.
  • Thresholding
  • Edge-based techniques
  • Region-based segmentation
  • Classification
5. Registration of different imaging modalities
  • Registration methodology: introduction, concepts and algorithms
  • Techniques and applications of rigid registration.
  • Techniques and applications of nonrigid registration.
6. Advanced visualization techniques
  • Indirect volume rendering techniques
  • Direct volume rendering techniques
  • Visualization of fused data
  • Visualization of vector fields.
  • Integrated surface and volume visualizations.

DOCENT METHODOLOGY
The course will be divided in lectures, projects and practical exercises.
Lectures: theoretical sessions, in which the basic concepts will be met. Reference books and articles about these topics will be used.
Projects: based on books and articles, synthesis projects will be proposed in order to be exposed in class.
Optionally, practical exercises about implementation of some of the methods presented in class will be proposed.
A validation test will be done to guarantee that students have reached the basic knowledge.
There is no lab.

EVALUATION METHODOLOGY
The final mark will be obtained from the projects and exercises and the validation test.

BIBLIOGRAPHY
The Visualization Handbook
Edited by Charles D. Hansen
Chris R.Johnson

The Visualization Toolkit
An Object-Oriented Approach to 3-D Graphics (2nd Edition) (Hardcover)
William Schroeder, Ken Martin, Bill Lorensen

Scientific Visualization: Overviews, Methodologies, and Techniques
Gregory M. Nielson, Hans Hagen, Heinrich Muller, Heinrich Mueller

Visualization and Processing of Tensor Fields
Joachim Weickert and Hans Hagen,
Springer 2005

Medical Image Registration
J.V.Hajnal, D.L.G.Hill, D.J.Hawkes
CRC Press LLC, 2001

Handbook of Medical Imaging, Volume 2:
Medical Image Processing and Analysis
Editors: M. Sonka and J. Michael Fitzpatrick
SPIE, Belligham, WA, 2000

Digital Image Processing
R.C.Gonzalez, R.E.Woods
Prentice Hall, 2002

Introduction to Information Theory and Data Compression
D.Hankerson, G.A.Harris, P.D.Johnson Jr.
CRC Press, 1998

RESOURCES
Appart from the textbooks recommended in the bibliography and a series of basic articles, students will have access to the PowerPoint presentations used for theoretical lectures.

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