The students will be able to explain the physical principles of MRI and functional MRI imaging for exploration / estimation of the physiological and morphological parameters (e.g. k-space and pulse sequences, tensor estimation and eigen-decomposition, deconvolution, compartment modeling, statistical modeling, and geometric modeling). Students will also achieve practical knowledge of software and algorithms for quantitative analysis of image-based information in space and time, and be able to install and modify these programs for use in analysis and visualization of their own data. This knowledge is particularly linked to MATLAB and Python.
After completion of the course the student should be able to:
Present knowledge about
Skills and general competence
Lectures + programming lab and demonstrations. Term and project-task. Course materials, including links to software and data, are available from the course web page.
ELMED219 (2 ECTS)
HUFY372
Webpage:
http://sites.google.com/site/bmed360
References:
Paul Tofts (Ed.) Quantitative MRI of the Brain: Measuring Changes Caused by Disease http://eu.wiley.com/WileyCDA/WileyTitle/productCd-0470014296.html
Jirsa VK, McIntosh AR (Editors) Handbook of Brain Connectivity.
http://www.springerlink.com/content/978-3-540-71462-0 .
Gonzalez RC, Woods RE. Digital Image Processing, 3rd ed., Prentice Hall, 2008
http://www.imageprocessingplace.com
Gonzalez RC, Woods RE, Eddins SL. 2nd ed. Digital Image Processing Using MATLAB, Prentice Hall, 2009. http://www.imageprocessingplace.com
Department of Biomedicine
studie@biomed.uib.no
Course coordinator:
Arvid Lundervold, http://uib.no/persons/Arvid.Lundervold