Digital image analysis for scientific applications 2018

ECTS credits: 8 for the whole course, 5 for a shorter version
Course period: October-December 2018
Lectures and computer exercises will be given on Tuesdays and Wednesdays.

Schedule, (fixed dates but the content may change).

Aim of course: This course aims at giving doctoral students from different disciplines sufficient understanding to solve basic computerized image analysis problems. The course will also offer an introduction to a number of freely available software tools (CellProfiler, ImageJ and ilastik), preparing the students to start using computerized image analysis in their own research.

Contents, study format and form of examination:
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 starts with basic computerized image analysis methods and computer exercises, including computerized image analysis research methodology and computerized image analysis research ethics. In the second part of the course, participants choose at least four lectures to tailor the course to match their own research interest.

The examination will be 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
Target group/s and recommended background:
The target group is graduate students from all subjects where computerized image analysis is (or could be) used as a research tool.

Application from course participants should be sent to Robin Strand, not later than September 1 2018.

Course coordinators: Robin Strand, and Carolina Wählby,, Centre for Image Analysis, Division of Visual Information and Interaction, Dept. of Information Technology, Uppsala University.

Detailed content for the 5 credits course
Detailed content for the 8 credits course
Detailed course information