ECTS credits: 8 for the whole course, 5 for a shorter version
Course period: October-December 2020
Lectures and computer exercises will be given online on Tuesdays and Wednesdays, starting from October 6 to December 2 (weeks 41-49).
The course will be given remotely via Zoom and Studium. More information will be sent to registered participants in September.
Schedule v2 - it may still change!
This course aims at giving doctoral students and researchers 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 participants 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:
The target group is graduate students and researchers from all subjects where computerized image analysis is (or could be) used as a research tool. Potential participants who are not affiliated with a Swedish university will be able to join the course pending the number of participants. We will provide information on space availability after the deadline for application.
Application from course participants should be sent to Damian Matuszewski, firstname.lastname@example.org not later than September 21.
Course coordinator: Damian Matuszewski, email@example.com
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