Teaching Methodologies
The teaching methodologies provide the acquisition of theoretical concepts, the resolution of examples applied to biomedical imaging and the development of projects applied to real cases. In lectures the teaching methodology is mainly expositive, complemented by the resolution and analysis of exercises. The laboratory classes allow the consolidation of theoretical knowledge through guided resolution and analysis of the results ofthe proposed exercises. In the research component students choose one of the proposed themes, and draw up a presentation for colleagues, giving rise to exchange of opinions on the subject. At the end of the semester the students develop a project that allows the consolidation of theoretical and practical knowledge
Learning Results
Familiarization with processing and analysis of digital images and its major areas of application. Acquire the concepts, techniques and main processing methods and image analysis for understanding, identifying andformulating strategies for solving problems that arise in the area of medical imaging.
Explore visualization and manipulation software for medical imaging. Know the advantages and risks of Diagnostic Computer Aided Systems.Develop habits of selflearning, of work in group and of oral communication.
Program
1. Introduction to Digital Image Processing
– Digital image processing – the main application areas
– Overview of digital image processing
-Main Components of a digital image processing system
2. Fundamental Concepts of Digital Imaging
Image formation
-The human vision system
-The medical image
-Image digitization: sampling and quantization
-Quality of the digital image
-Relations between pixels, neighborhoods, adjacency, connectivity, distance measurements
3. Image Processing in Spatial Domain
-Grey Level transformations
-Histogram Processing
-Enhancement of the image
-Spatial Filters
-Image Restoration
4. Morphological image processing
5. Analyses, Image Representation and Description
-Segmentation
-Processing of Shape and Texture Analysis
6. Software for Manipulation and Visualization of Medical Images
7. Computer Aided Diagnosis Systems Based on Image Analysis
Curricular Unit Teachers
Internship(s)
NAO