Course syllabus

Medicinsk bildanalys
Medical Image Analysis

FMAN30, 7,5 credits, A (Second Cycle)

Valid for: 2020/21
Decided by: PLED F/Pi
Date of Decision: 2020-04-01

General Information

Elective for: BME4-sbh, BME4-br, C5, D4, E4-mt, F4, F4-bg, F4-bm, Pi4-biek, Pi4-bam, MMSR2
Language of instruction: The course will be given in English on demand


The main aim of the course is to give a basic introduction to theory and mathematical methods used in medical image analysis, to an extent that will allow the student to handle medical image processing problems. In addition the aim is to make the student develop his or her ability in problem solving, both with or without a computer. A further aim is to prepare the student for further studies and research in the border area between medicin and engineering.

Learning outcomes

Knowledge and understanding
For a passing grade the student must

Competences and skills
For a passing grade the student must


Basic concepts: Images, volume data, 4D data, pixels and voxels, file-formats, DICOM (Digital Imaging and Communications in Medicine). .

Image acquisition techniequs: Radiography, CT (x-ray Computed Tomography), MR (Magnetic Resonance imaging), ultrasound, PET (Positron Emission Tomography), Scint (Scintigraphy) and SPECT (Single-Photon Emission Computed Tomography).

Noise and Image enhancement, lossless compression

Registration: Registration of medical images. Mutual information. Landmark based methods. Deformation models.

Segmentation: Active contours in 2D, 3D and 4D, active appearance models (AAM). Graph-methods.

Machine Learning: Training, testing, generalization, hypothesis spaces.

Validation: Databases. Ethics.


Examination details

Grading scale: TH - (U,3,4,5) - (Fail, Three, Four, Five)
Assessment: Compulsory assignments and oral exam.

The examiner, in consultation with Disability Support Services, may deviate from the regular form of examination in order to provide a permanently disabled student with a form of examination equivalent to that of a student without a disability.


Assumed prior knowledge: FMAN20 Image Analysis or corresponding knowledge.
The number of participants is limited to: No

Reading list

Contact and other information

Course coordinator: Anders Holst,
Course administrator: Studerandeexpeditionen,
Teacher: Kalle Åström,
Course homepage: