Ender Konukoglu: Katalogdaten im Herbstsemester 2017
|Name||Herr Prof. Dr. Ender Konukoglu|
ETH Zürich, ETF E 113
|Telefon||+41 44 633 88 16|
|Departement||Informationstechnologie und Elektrotechnik|
|Beziehung||Assistenzprofessor (Tenure Track)|
|227-0391-00L||Medical Image Analysis|
Findet dieses Semester nicht statt.
|3 KP||2G||E. Konukoglu|
|Kurzbeschreibung||It is the objective of this lecture to introduce the basic concepts used |
in Medical Image Analysis. In particular the lecture focuses on shape
representation schemes, segmentation techniques, and the various image registration methods commonly used in Medical Image Analysis applications.
|Lernziel||This lecture aims to give an overview of the basic concepts of Medical Image Analysis and its application areas.|
|Voraussetzungen / Besonderes||Basic knowledge of computer vision would be helpful.|
|227-0447-00L||Image Analysis and Computer Vision||6 KP||3V + 1U||L. Van Gool, O. Göksel, E. Konukoglu|
|Kurzbeschreibung||Light and perception. Digital image formation. Image enhancement and feature extraction. Unitary transformations. Color and texture. Image segmentation and deformable shape matching. Motion extraction and tracking. 3D data extraction. Invariant features. Specific object recognition and object class recognition.|
|Lernziel||Overview of the most important concepts of image formation, perception and analysis, and Computer Vision. Gaining own experience through practical computer and programming exercises.|
|Inhalt||The first part of the course starts off from an overview of existing and emerging applications that need computer vision. It shows that the realm of image processing is no longer restricted to the factory floor, but is entering several fields of our daily life. First it is investigated how the parameters of the electromagnetic waves are related to our perception. Also the interaction of light with matter is considered. The most important hardware components of technical vision systems, such as cameras, optical devices and illumination sources are discussed. The course then turns to the steps that are necessary to arrive at the discrete images that serve as input to algorithms. The next part describes necessary preprocessing steps of image analysis, that enhance image quality and/or detect specific features. Linear and non-linear filters are introduced for that purpose. The course will continue by analyzing procedures allowing to extract additional types of basic information from multiple images, with motion and depth as two important examples. The estimation of image velocities (optical flow) will get due attention and methods for object tracking will be presented. Several techniques are discussed to extract three-dimensional information about objects and scenes. Finally, approaches for the recognition of specific objects as well as object classes will be discussed and analyzed.|
|Skript||Course material Script, computer demonstrations, exercises and problem solutions|
|Voraussetzungen / Besonderes||Prerequisites: |
Basic concepts of mathematical analysis and linear algebra. The computer exercises are based on Linux and C.
The course language is English.