Computer Graphics


Computer Vision (Sem. 1)

Learning outcomes

To introduce the state-of–the-art in medical Imaging technology, providing an overview of standards,
techniques, equipment and applications. Promote the analyses of practical cases and the simulation of real
health environment situations.
Competences:
-Recognize the applications of information processing in medical imaging.
- Be familiar with the concepts associated with imaging systems, image processing, computer vision, pattern
recognition and computer modeling in medical imaging.
- Gain an appreciation for the use and development potential of the ImageJ and OsiriX applications.

Syllabus

1) Evolution of the field of medical imaging - Introduction, evolution towards digital modalities, medical
imaging equipment.
2) Manipulation and processing of medical imaging - Windowing, zoom, filters, segmentation, ROIs. Clinical
applications.
3) PACS, Picture archiving and Communication System - Architecture, storage technologies. DICOM standard,
workflow process and HIS/RIS integration. Practical realisations.
4) Multidimensional imaging -Image realignment and fusion, 3D reconstruction, Clinical applications.

Teaching methodologies and evaluation

The teaching methodology alternates theoretical lectures, practical tutorials and practical work supervision.
Evaluation has three components: written examination, individual practical assignments and group practical
assignments.
The written examination has a weight of 40% and evaluates the correction, clarity and structure of the answers,
as well as the ability to synthesize complex ideas and critical thinking.
The individual practical assignments (30%) include the Oral Presentation, the written report and the developed
work.
The group practical assignments (30%) include the Oral Presentation, the written report and the developed
work.

Bibliography

Paul Suetens, “Fundamentals of Medical Imaging”, 2ª,ED, Cambridge University Press, New York, 2009
Chris Guy, Dominic Ffytche, “An Introduction to – The Principles of Medical Imaging”, revised Edition, Imperial
College Press, 2005
Alex A.T. Bui, Ricky K. Taira, “Medical Imaging Informátics”, Springer, 2010
H. K. Huang, D.Sc., FRCR (Hon.), FAIMBE, “PACS and Imaging Informatics – Basic Principles and
Applications”,2ªEd., Wiley-Blackwell, 2010
Additionally, a set of contents supporting the theoretical lectures are also supplied to the students on the
Curricular Unit Web page.

Lighting and Visualisation I (Sem. 1)

Learning outcomes

Characterize the graphics pipeline and the associated data flow. Identify the programmable components and
their purpose;
Produce shader code to run on GPUs;
Design, implement and evaluate solutions based on GPU programming using shading languages;
Evaluate local illumination algoritms and other graphical effects on the suitability of a GPU implementation and
performance issues;
Aditionally, the following soft skill should also be developed: exhibit adequate oral and written communication
capabilities, promoting language as a tool for expression and development of autonomous ideas and
arguments, grounded on critical thinking.

Syllabus

• The history and current features of the graphics pipeline;
• GPU programming with GLSL;;
• Local illumination methods and graphical effects, and their GPU implementation.
• Profiling GPU solutions.

Teaching methodologies and evaluation

Theoretical classes to cover the fundamentals of GPU programming, including an overview of the graphics
pipeline, as well as local illumination algorithms and other graphical effects. These sessions are
complemented with discussion with the students of implementation case studies.
Practical classes are hands-on, to allow the students to fully grasp the little details of GPU programming
Evaluation:
50% practical assignment; 50% position paper, and respective oral presentation, with respect to some seminal
paper in this area of knowledge.

Bibliography

Real Time Rendering ;Tomas Akenine-Moller, Eric Haines, Naty Hoffman ; AK Peters; 3rd edition, 2008
Mathematics for 3D Game Programming and Computer Graphics;Eric Lengyel;Delmar Cengage Learning
Publishing; 3rd edition; 2011

Lighting and Visualisation II (Sem. 2)

Learning outcomes

Characterize global illumination and describe the various stages of the rendering and visualization process;
Explain the rendering equation and explain the meaning of each of its factors;
Relate the various global illumination algorithms with the general model sustained by the rendering equation,
inferring which lighting phenomena are modelled;
Design, implement and assess new solutions for the global illumination problem;
Recognize functional and performance limitations associated with each global illumination algorithm;
Aditionally, the following soft skill should also be developed: exhibit adequate oral and written communication
capabilities, promoting language as a tool for expression and development of autonomous ideas and
arguments, grounded on critical thinking.

Syllabus

• Local and global illumination models, both empirical and physically based (Phong, Cook-Torrance, Ward);
• Radiometry and Photometry;
• Light transport mechanisms, the BRDF and the rendering equation;
• Global ilumination Algorithms: Ray tracing (Classical, distributed and Monte Carlo), radiosity, photon
mapping.

Teaching methodologies and evaluation

10 hours (on a total of 45) are dedicated to lecturing sessions, where the fundamenthal theory is presented.
These are complemented with 20 hours of hands-on tutorials, where global illumination algorithms are
developed and evaluated.
Around 10 hours are dedicated to discussions with students, where they are expected to be critical about the
contents they have been exposed to, fostering the identification of limitations and the proposal of extensions
to the algorithms.
The remaining 5 hours are dedicated to evaluation, as described below.
Evaluation:
50% written examination; 50% position paper, and respective oral presentation, with respect to some seminal
paper in this area of knowledge.

Bibliography

Physically Based Rendering: from Theory to Implementation; Matt Pharr and Greg Humphreys; Morgan
Kaufmann; 2nd edition, 2010
Advanced Global Illumination; Dutré, P., Bala, K. e Bekaert, P.; AK Peters, 2006

Technologies and Applications (Sem. 2)

Learning outcomes

Understand the usage of OpenGL in an HTML context;
Design and develop computer graphics applications in a web environment;
Design and develop solutions for data streaming and web services;
Design, analyse and develop a virtual globe support architecture ;
Analyse solutions regarding performance, quality and conformity with the browsers;
Aditionally, the following soft skill should also be developed: exhibit adequate oral and written communication
capabilities, promoting language as a tool for expression and development of autonomous ideas and
arguments, grounded on critical thinking.

Syllabus

• HTML5, WebGL and their interopreability;
• Developing computer graphics application in a web environment;
• Streaming and web services data flow solutions;
• Virtual Globes application architecture;
• Browser conformity, quality and performance analisys.

Teaching methodologies and evaluation

Theoretical classes to cover the particular issues regarding the usage of computer graphics in web
applications. These sessions are complemented with discussion with the students of implementation case
studies.
Practical classes are hands-on, to allow the students to fully grasp the little details of GPU programming
Evaluation:
50% practical assignment; 50% position paper, and respective oral presentation, with respect to some seminal
paper in this area of knowledge.

Bibliography

HTML5 A vocabulary and associated APIs for HTML and XHTML, W3C Working Draft,
http://www.w3.org/TR/html5/
Rost, R. J. (2006). OpenGL Shading Language. Interface (pp. 1-36). Addison-Wesley Professional. Retrieved
from http://www.opengl.org/documentation/glsl/
Wolff, D. (2011). OpenGL 4.0 Shading Language Cookbook. Language (p. 340). Packt Publishing. Retrieved
from http://dl.acm.org/citation.cfm?id=2049800