Graduate courses

1. Scientific Data Presentation, 2 hp 
   Cris Luengo
   Period: 150504-0508 
   Venue: The course was given at the UU Hospital.
   Description: The goal of the course is to give PhD students the ability to effectively present the data resulting from their experiments. This is a very important form of communication for any researcher, just as important as writing and speaking.

2. Application Oriented Image Analysis, 5/8 hp 
   Ida-Maria Sintorn, Robin Strand, Carolina Wählby, Damian Matuszewski, Nataša Sladoje, Filip Malmberg 
   Period: 151006-1201 
   Venue: The course was given at CBA.
   Description: This course aims at giving doctoral students from across the faculty sufficient understanding to solve basic computerized image analysis problems. The course will also offer an introduction to a number of freely a vailable software tools, preparing the students to start using computerized image analysis in their own research.

   The focus of the course is on reaching a broad understanding of computerized image analysis and a basic understanding of the theory and algorithms behind the computerized image analysis methods. The course contained computerized image analysis methods and computer exercises, including computerized image analysis research methodology and computerized image analysis research ethics. The examination was divided into

   • three computer exercises, both to get familiar with the interfaces of common software and to solve realistic image processing problems,
   • a written exam on part 1,
   • a project (oral presentation and written report), where the course participants apply the collected knowledge to a project within their own domain,
   where the first to items were required for 5 credits and for all three items, the course gave 8 credits.

3. Classical & Modern Papers 
   PhD students at CBA, Cris Luengo and Nataša Sladoje 
   Period: During the whole year
   Venue: The course was given at CBA.
   Description: Presentations and discussions of classical or modern papers in image processing. 
4. SSBA Summer School: Image Processing Using Graphs 
   Filip Malmberg and Johan Nysjö 
   Period: 150818-150820
   Venue: The course was given at CBA.
   Description: In recent years, graphs have emerged as a unified representation for image analysis and processing. Many powerful image processing methods have been formulated on pixel adjacency graphs, i.e., a graph whose vertex set is the set of image elements (pixels), and whose edge set is determined by an adjacency relation among the image elements. Due to its discrete nature and mathematical simplicity, this graph based image representation lends itself well to the development of efficient, and provably correct, methods for image processing. This course gives an overview of recent developments in this field. Topics covered include graph-based methods for:
   • Combinatorial optimization
   • Image segmentation
   • Image registration and stereo matching
   • Classification and clustering

   The course was sponsored by the Swedish Society for Automated Image Analysis (SSBA).