Due to the COVID-19 crisis, the information below is subject to change,
in particular that concerning the teaching mode (presential, distance or in a comodal or hybrid format).
4 credits
30.0 h + 15.0 h
Q2
Teacher(s)
Macq Benoît;
Language
French
Main themes
A) Extension of the signal notion to images - Basics on main medical imagers - Main features of medical images B) Introduction to medical images processing - Filtering methods - Basics on mathematical morphology - Analysis and segmentation C) Viewing algorithms - Surfaces viewing - Volumes viewing - Animation D) Implementation - Introduction to coding and transmission - Software integration E) Applications - 2D imagery - 3D imagery.
Aims
At the end of this learning unit, the student is able to : | |
| 1 | This class is devoted to the methods of medical images quantitative analysis. The theory is illustrated with exercices and demonstrations including examples of anatomical and functional medical images processing. |
Content
Basics on main medical imagers. Notion of signal; extension to images. Main features of medical images. Introduction to medical images processing. Filtering methods. Basics on mathematical morphology. Analysis and segmentation. Viewing algorithms. Surfaces viewing. Volumes viewing. Animation. Implementation. Introduction to coding and transmission. Software integration. Applications. 2D imagery. 3D imagery.
Other information
Prerequisite: a signal processing class (e.g.: SBIM 2241 Biomedical signals acquisition and processing). As indicated, basics on main medical imagers (e.g.: INIS 2103 Medical imaging) will be briefly recalled in the introduction.
Oral examination
Faculty or entity
SBIM
Programmes / formations proposant cette unité d'enseignement (UE)
Title of the programme
Sigle
Credits
Prerequisites
Aims
Master [120] in Statistic: Biostatistics
