Digital Image Analysis for Scientific Applications


ECTS credits: 8 for the whole course, 5 for a shorter version


Course period: October-December 2018


Maximum number of participants: 40


Aim of the course

Today, many research projects at the TekNat Faculty, in areas as diverse as biology, chemistry, materials science, and astronomy, require imaging and the analysis of images[1]. Digital image analysis (IA) has become an indispensable tool for objective, quantitative and fast analysis of large amounts of image data. Such analyses are often needed to extract specialized knowledge and increase the scientific value of image-based experiments. A number of IA tools are available, but in order to use them in a correct and meaningful way, a basic understanding of the underlying methods is necessary. This course aims at giving doctoral students from across the faculty sufficient understanding to solve basic IA problems. The course will also offer an introduction to freely available software tools, as well as Matlab, preparing the students to start using IA in their own research.

Students from the research subject computerized image analysis are not expected to take this course.


Contents, study format and form of examination

The focus of the course is on reaching a broad understanding of IA and a basic understanding of the theory and algorithms behind the IA methods. The course starts with basic IA methods and computer exercises, including IA research methodology and IA research ethics. In the second part of the course, participants choose at least four lectures/computer exercises to tailor the course to match their own research interest (see Fig 1).

The examination will be divided into

The course participants will study literature relevant to their project, practice their ability to scientific analyses, find and test appropriate IA methods, and present and discuss their scientific results. The course participants will get eight credits for taking the whole course, or five credits for taking part 1.


Content for the 5 credits course


Content for the 8 credits course



Figure 1: Course structure. The first part gives 5 ECTS credits, and the whole course, part I and II, gives 8 ECTS credits. The lectures in the second part will be adjusted to match the students’ research interest. We will invite guest lecturers when needed.


Targeted groups and recommended background

The target group is graduate students from all subjects where IA is used as a research tool. No previous experience in IA is required from the course participants, but an interest in its potential as a tool in their own research is important. The course can be followed with a basic knowledge of mathematics (corresponding to uppersecondary level entry requirements) and basic computer skills.

In the second part of the course, we plan to have a set of lectures focused on IA usage in the research domains in which we have extensive experience and for which we expect many students: microscopy, radiology, materials science and medical engineering. To match all students’ interests, we will use our IA network and tailor lectures/literature suggestions to fit specific research areas where IA is used.

By using this flexible structure, we will attract students from all sections within the TekNat Faculty, including life science, medical engineering, and materials science.


Department with main responsibility

Dept. of Information Technology, Division of Visual Information and Interaction, Vi2


Course coordinators

Robin Strand,

Carolina Wählby,


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


[1]See the research projects, list of publications and list of cooperation partners in the Centre for Image Analysis Annual report,