Program Overview

Program Overview

The University of Copenhagen offers a Master's program in Medical Image Analysis (MIA), which is designed to provide students with a comprehensive understanding of medical image formation, analysis, and applications.

Program Description

The MIA program is aimed at students from computer science, physics, and mathematics with an interest in medical image analysis and related technologies. The program covers various topics, including:

• Physics of X-ray formation
• Computed tomography
• Magnetic Resonance Imaging
• Functional MRI
• Positron Emission Tomography
• Single Photon Emission Tomography
• Medical statistics
• Segmentation/Pixel classification
• Shape modelling and statistics
• Rigid & Non-rigid registration + Multi-modal registration
• Machine learning with medical data
• Applications in lung diseases
• Applications in neurology

Learning Outcomes

Upon completion of the program, students will have acquired:

Knowledge of

• Physics of X-ray formation
• Computed tomography
• Magnetic Resonance Imaging
• Functional MRI
• Positron Emission Tomography
• Single Photon Emission Tomography
• Medical statistics
• Segmentation/Pixel classification
• Shape modelling and statistics
• Rigid & Non-rigid registration + Multi-modal registration
• Machine learning with medical data
• Applications in lung diseases
• Applications in neurology

Skills in

• Explaining the basics of the underlying physics behind medical image acquisition techniques
• Explaining the role of medical image analysis in relation to detection and prognosis of pathologies and clinical investigations
• Reading and implementing methods described in the scientific literature in the field of medical imaging
• Finding and using existing tools within medical image analysis and assessing the quality of the output produced
• Applying the implemented methods to medical images with the purpose of analysing a specific pathology

Competences in

• Analysing, creating, and using pipelines of methods for the purpose of analysing medical images in a scientific context
• Understanding the fundamental challenges in medical image analysis
• Understanding the representation of images in a computer

Program Structure

The program consists of lectures, exercises, and assignments, with a total workload of 206 hours.

Assessment

The program is assessed through a combination of written assignments and an oral exam. Students must hand in four written assignments, and the oral exam will be based on one of these assignments chosen at random by the examiner.

Program Details

• Language: English
• Course code: NDAK10005U
• Credit: 7.5 ECTS
• Level: Full Degree Master
• Duration: 1 block
• Placement: Block 1
• Schedule: A
• Course capacity: No limitation
• Study board: Study Board of Mathematics and Computer Science
• Contracting department: Department of Computer Science
• Contracting faculty: Faculty of Science
• Course Coordinators: Melanie Ganz-Benjaminsen
• Lecturers: Melanie Ganz & Bulat Ibragimov

Recommended Academic Qualifications

Students are expected to have a mature and operational mathematical knowledge, including linear algebra, geometry, basic mathematical analysis, and basic statistics. Programming skills in Python are highly recommended. Academic qualifications equivalent to a BSc degree are recommended.