The Course at a Glance:

ECTS credits: 5.0

Teaching language: English

Course offered (semester): Fall + Spring (the course will be held when at least two students apply)

Lectures (7 x 2 hrs):

- Introduction to modelling, MRI and image processing

- Water diffusion and diffusion tensor MR Imaging (MR-DTI)

- Blood perfusion and dynamic susceptibility contrast MR imaging (DSC-MRI)

- Vascular permeability and T1-weighted dynamic contrast enhanced MRI (DCE-MRI)

- Special topic (e.g. Introduction to systems biology; Consciousness, resting state fMRI and neurodynamics)

Demonstrations / computer labs (6 x 2 hrs):

- Image processing in MATLAB

- Processing of diffusion tensor MR imaging data using MATLAB and other software

- Processing of dynamic susceptibility contrast MR images (DSC-MRI)

- Vascular permeability mapping and Dynamic T1-weighted Contrast Enhanced MRI

Prerequisites: The same as the entrance-requirements for the master study in human biology.

Recommended Qualifications: Parts of courses in general human physiology (HUFY225/MED1FYS) dealing with diffusion, perfusion and microcirculation. Basic course in brain anatomy and neurophysiology (HUFY235/MED1NEVRO), and in molecular and cell biology (e.g. MOL100, MOL200, HUCEL362) . Some background and interest in mathematics (e.g. calculus & linear algebra) and some experience with using computers in biomedical applications (e.g. statistical packages, signal processing, etc.). Access to a computer with MATLAB and Image Processing Toolbox installed.

Assessment / final exam:

Oral presentation of personal project (20 min. + 5 min. discussion).   Grading: A, ..., F

Course Coordinator: Arvid Lundervold, Department of biomedicine, Neuroscience Research Group  -  Studieseksjonen. Tel: (+47) 55 58 64 40 studie@biomed.uib.no

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Course details:

Core textbook:  

Paul Tofts (Editor)

Quantitative MRI of the Brain:

Measuring Changes Caused by Disease.

ISBN: 0-470-84721-2, Hardcover, 650 pages

Wiley, August 2003 [Especially chapters: 1, 7, 10, 11] 

ONLINE edition  (See also qmri.org)

                                              LECTURES

Lec1   Introduction to modelling, MRI and image processing  

(Tofts Ch.1, Ch.2 pp.17-23,38-49)

Basic principles and applications of magnetic resonance in physiological imaging

Some mathematics and statistics needed in biomedical image processing and analysis

Lec2   Water diffusion and diffusion tensor MR Imaging (MR-DTI)  (Part 1)

Physical principles and biological contrast mechanisms  (Tofts Ch.7 pp.203-213,218-221)

Measurement and estimation of the diffusion tensor

(Tofts Ch.7 pp.213-218,221-228,231-232)

Lec3   Water diffusion and MR-DTI  (Part 2)

Eigenvalues and eigenvectors of the diffusion tensor – diffusion anisotropy measures

Advanced processing and applications of DTI – fiber tracking 

(Tofts Ch.7 pp.228-231,244-249)

Lec4  Blood perfusion and dynamic susceptibility contrast MR imaging (DSC-MRI) (Part 1)

Tracer kinetics and first pass bolus tracking – the model (Tofts Ch.11 pp.365-379)

Perfusion imaging of the brain – applications (Tofts Ch.11 pp.390-402)

Lec5   Blood perfusion and DSC-MRI  (Part 2)

Tracer kinetics and bolus tracking – measurement & computation 

(Tofts Ch.11 pp.379-390)

Estimation and visualization of perfusion parameters - rCBV, rCBF, rMTT

Lec6   Vascular permeability and T1-w dynamic contrast enhanced MRI (DCE-MRI)

Pharmacokinetic compartment analysis in DCE-MRI – the model

(Tofts Ch.10 pp.341-350)

Estimation and visualization of pharmacokinetic model parameters 

(Tofts Ch.10 pp.350-360)

Lec7   Special topic:   "On consciousness, resting state fMRI, and neurodynamics" (cf. http://www.nonlinearbiomedphys.com/content/4/S1/S9)

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                       COMPUTER LABS / DEMONSTRATIONS

                       Data can be downloaded from here

Lab1  Image processing in MATLAB

           Introduction to MATLAB

           The Image Processing Toolbox – reading, display and writing of images

Lab2   Multispectral analysis and tissue classification

              Unsupervised classification: K-means clustering

              Supervised classification: Nearest neighbour

Lab3   Processing of diffusion tensor MR imaging data using MATLAB  and other SW

              Reading DTI into MATLAB

              Computing the diffusion tensor

Lab4   Processing of dynamic susceptibility contrast MR image (DSC-MRI) data (Part 1)

              Reading and displaying image time series in MATLAB

              Detection and corrections of noise, movements and recirculation effects

Lab5   Processing of DSC-MRI data (Part 2)

             Tracer concentration time courses, the arterial input function, 

              and deconvolution methods

             Determination of blood volume, blood flow and mean transit time 

             (rCBV, rCBF, and rMTT)

Lab6    Pharmakokinetic modeling – curve fitting – parameter estimation