Recommended prerequisite for participation in the module

Content, progress and pedagogy of the module

Learning objectives

Knowledge

Students who complete the module:

• Have knowledge of basic and advanced image analysis and computer vision methods and concepts 
• Have knowledge of data driven and model based techniques for analysis of 2D or 3D image data
• Have knowledge of optical and tomographic imaging geometry
• Have knowledge of linear and non-linear techniques for solving inter-subject and intra-subject image registration problems
• Have knowledge of geometrical representation of objects in 2D and 3D derived from image data
• Have knowledge of statistical and morphological image processing
• Have knowledge of multi-scale techniques

Skills

• Are able to apply image analysis and computer vision methods to extract information from the original image data 
• Are able to apply intensity transformations and image filtering in the spatial and frequency domain
• Are able to detect fundamental image features from image data
• Are able to apply basic 2D and 3D image segmentation methods
• Can solve linear image registration problems

Competences

• Are able to demonstrate understanding of the concepts, theories and techniques in the area of image analysis and computer vision
• Are able to apply methods on medical image data to extract quantitative and qualitative anatomical and physiological information

Type of instruction

Lectures and exercises.

Exam

Exams

Additional information

Please contact the   programme student counsellors if you consider applying to the education and you have questions.

Please consult the Moodle page for your semester and contact the semester coordinator if you have academic questions, or the study secretary if you have administrative questions.

All other enquiries may be directed to Malene Møller Knudsen, secretary of the Study Board.