Please note! Course description is confirmed for two academic years (1.8.2018-31.7.2020), which means that in general, e.g. Learning outcomes, assessment methods and key content stays unchanged. However, via course syllabus, it is possible to specify or change the course execution in each realization of the course, such as how the contact sessions are organized, assessment methods weighted or materials used.
At the end of the course, the students shall have familiarized themselves with core concepts and theory of imaging, and applied these concepts by analyzing imaging systems and estimating/reconstructing various images. Meanwhile, students have also learned problem solving, algorithmic thinking, mathematical programming, information visualization, collaborative working, and reporting.
Schedule: 10.09.2020 - 04.12.2020
Teacher in charge (valid 01.08.2020-31.07.2022): Matti Stenroos
Teacher in charge (applies in this implementation): Matti Stenroos
Contact information for the course (applies in this implementation):
CEFR level (applies in this implementation):
Language of instruction and studies (valid 01.08.2020-31.07.2022):
Teaching language: English
Languages of study attainment: English
CONTENT, ASSESSMENT AND WORKLOAD
This is a course on principles of imaging: image reconstruction (inverse problem), analysis of linear imaging systems, and physical mechanisms of image formation. These principles are illustrated through some tomographic and electromagnetic biomedical imaging methods.
Assessment Methods and Criteria
Teaching Methods: Lectures that introduce concepts and prepare for exercises; exercises done in small groups and reported individually; individual essays and other written reports; feedback.
Assessment Methods and Criteria: The course requires active participation throughout the semester. The grading is based on exercise solutions (appr. 80%) and other written reports (appr. 20%). There are appr. five exercise reports and five other reports to be returned along the semester; all reports must be timely handed in.
- Lectures: 10-11 x 2h
- Exercise sessions: 10-18 x 2 h
- Self / small-group study: 75-95 h
The course material consists of lecture slides and/or notes and exercise problems. Students are expected to find further information themselves. The key material, exercise solutions and reports, will be produced by students.
Bachelor-level courses in physics and mathematics, basic Matlab skills (scripting, writing own functions, plotting).