Single-Course English 5 ECTS

3D imaging, analysis and modelling

Overall Course Objectives

CT scanners have become an important tool for imaging of 3D structures in many different materials. Examples are quality assurance of building materials, of food, or of complex 3D design, for example produced by a 3D printer. In the health sector, CT scanners are often used for diagnosing, but new tools and drugs are also scanned when their 3D structures are important. Micro- or nano-CT scanners are more and more used within research and development of new materials. 3D image analysis is also an interesting field under rapid development for applied mathematics and programming.

This course is an introduction to anyone who would like to work with this technology, i.e. with 3D imaging and analysis of 3D data. The course will educate users of advanced 3D x-ray imaging methods and prepare students to work with 3D data.

The students will in groups work with scanning and analyzing a material. In this work the groups will be guided through the following process: data acquisition in the lab, reconstruction of the acquired data, analysis of 3D data and modelling of physical properties. In this way, the students will achieve knowledge on the type of information that can be extracted from 3D data and how it is done in practice.

The course will provide a basis for later individual project work (BSc, MSc, PhD) with 3D analysis in the direction in which the student is specializing.

Learning Objectives

  • Explain the principle behind x-ray CT
  • Plan and execute a project on 3D structures in a given material
  • Describe the experimental set-up for 3D x-ray imaging
  • Explain how x-rays interact with materials
  • Perform x-ray CT experiments
  • Explain principles of reconstruction methods
  • Apply reconstruction algorithms to convert 2D images into a 3D dataset
  • Perform filtering and segmentation of 3D data
  • Identify parameters that can be measured in a 3D dataset
  • Apply quantitative measurement methods to extract statistically valid information from 3D data sets
  • Apply modelling of physical properties of a material in 3D
  • Report and communicate research results in a clear and concise manner

Course Content

The course is based on project-organized learning. Throughout the course, the students will work in groups. Each group is given a material which they will work with. In the groups, the students decide which information is relevant to extract from the 3D structure of their material, and what kind of modelling they would like to perform. In the lab, the groups will use an x-ray CT scanner to record data that they reconstruct, segment and analyze. The last part of the analysis will be to apply modelling of physical properties of a material in 3D. To support the project-organized learning, theoretical lectures, online material such as videos and small exercises will be given. The lectures and videos will describe the principles behind each practical step (x-ray experiment, reconstruction, segmentation, analysis, modelling). The course provides students with a basic understanding of and skills to operate x-ray CT scanners as well as relevant software for reconstruction and analysis. The students will exercise their skills in data analysis. Across the groups, the students will interact by giving oral presentations and feedback.

Recommended prerequisites

02631/02632/02633/02692, Basic programming skills, for example in Matlab or Python

Teaching Method

Project-organized learning. Lectures, oral presentations, group work, lab exercises, computer exercises.
The course will be evaluated through the course period.
Relevant safety procedures will be introduced during the course.


Limited number of seats

Minimum: 10, Maximum: 24.

Please be aware that this course has a minimum requirement for the number of participants needed, in order for it to be held. If these requirements are not met, then the course will not be held. Furthermore, there is a limited number of seats available. If there are too many applicants, a pool will be created for the remainder of the qualified applicants, and they will be selected at random. You will be informed 8 days before the start of the course, whether you have been allocated a spot.

See course in the course database.





13 weeks




DTU Lyngby Campus

Course code 47209
Course type Bachelor
Semester start Week 35
Semester end Week 48
Days Thurs 8-12

7.500,00 DKK

Please note that this course has participants limitation. Read more