Basic Mathematical Methods for Imaging and Visualization (IN2124)
Course 240918393 in WS 2017/8
General Data
| Course Type | Lecture w/ Exercise |
|---|---|
| Semester Weekly Hours | 4 SWS |
| Organisational Unit | Informatics 16 - Chair of Computer Aided Medical Procedures (Prof. Navab) |
| Lecturers |
Tobias Lasser Assistants: Anca-Elena Stefanoiu |
| Dates |
Tue, 12:30–14:30 Mon, 16:00–18:00, Interims I 102 and 5 singular or moved dates |
Assignment to Modules
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IN2124: Grundlegende Mathematische Methoden für Imaging und Visualisierung / Basic Mathematical Methods for Imaging and Visualization
This module is included in the following catalogs:- Focus Area Imaging in M.Sc. Biomedical Engineering and Medical Physics
- Catalogue of non-physics elective courses
Further Information
Courses are together with exams the building blocks for modules. Please keep in mind that information on the contents, learning outcomes and, especially examination conditions are given on the module level only – see section "Assignment to Modules" above.
| additional remarks | In order to solve real-world problems in applied engineering areas of computer science, knowledge of basic mathematical tools is essential. The aim of this lecture is to provide a basic mathematical toolbox for selected topics of Imaging and Visualization. We will present the basic and most common mathematical techniques and use mostly applications from Computer Vision and Image Processing for illustration. The same mathematical tools, however, are also needed in many other engineering fields like Artificial Intelligence and Machine Learning, Computer Graphics, Robotics, and so on. The lecture will have three main parts: Basics, Tools and Practise. In the first part, we will give a reminder of linear algebra, analysis, geometry, probability and statistics basics. We go on by presenting the use of these basic concepts in methods such as parameter estimation and optimization. And finally, the students will have the opportunity to gain a deep understanding and hands-on experience of the methods by implementing them and/or using them to solve real-world problems during the exercises. |
|---|---|
| Links |
Course documents E-Learning course (e. g. Moodle) TUMonline entry |