Welcome to the (NOW OBSOLETE) Course site for HUFY 372  (visit: "BMED360" w/ 10 ECTS from Fall 2010)

See also http://www.uib.no/course/HUFY372 and the internal My Space / Mi side (for which an UiB account is needed),
The course is included in List A of the Norwegian Research School in Medical Imaging (http://www.medicalimaging.no).

[This Course website is established in the spirit of the Open science and the Reproducible research initiatives]

Structural and functional connectivity assessed with magnetic resonance imaging (MRI)
Image-derived information from a multi-modal MRI examination of a healthy volunteer in a larger study of “cognitive aging”, obtained automatically with different freely-available image processing and analysis tools. Coregistration (spatial alignment) of the different modalities was implemented in MATLAB. A T1-weighted anatomical 3-D image is superimposed with: (i) an anatomical region (thalamus) segmented with FreeSurfer (25 hrs processing time); (ii) a resting state networks (RSNs) derived from independent component analysis (ICA) analysis of the functional BOLD fMRI image time series; (iii) white matter fiber tracts (blue) between these regions of interest. Yellow “blob” represents the ventromedial prefrontal cortex (VMPFC) component of the default mode network (DMN). Lower traces show the corresponding time courses (256 frames; TR= 2 s) of the resting state components. Upper trace is IC-3 (DMN). Lower trace is IC-26 located in the central thalamic region (not part of the DMN). Lower right shows histogram of the diffusion tensor fractional anisotropy (FA) values, reflecting white matter integrity and structural connectivity along the fiber tracts between the two brain regions (a) spatial intersection between anatomical thalamus and the RSN defined by IC-26, and (b) the VMP
FC component of DMN defined by IC-3. Functional connectivity is measured by cross-correlation between time courses IC-3 and IC-26.  Data: Anatomy1.nii.gzAnatomy2.nii,gz, DWI.nii.gz, bvec.dat, bval.dat, Resting.nii.gz, Fingertapping.nii.gz
[See also Lundervold A. On consciousness, resting state fMRI, and neurodynamics. Nonlinear Biomedical Physics 2010,4(Suppl 1):S9  doi:10.1186/1753-4631-4-S1-S9 ]
 (Courtesy of Martin Ystad, Tom Eichele, Erlend Hodneland, and Judit Haasz)  [ga]

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

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)


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 trackingthe model (Tofts Ch.11 pp.365-379)

Perfusion imaging of the brainapplications (Tofts Ch.11 pp.390-402)

Lec5   Blood perfusion and DSC-MRI  (Part 2)

Tracer kinetics and bolus trackingmeasurement & 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)

                       COMPUTER LABS / DEMONSTRATIONS

                       Data can be downloaded from here

Lab1  Image processing in MATLAB

           Introduction to MATLAB

           The Image Processing Toolboxreading, 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 modelingcurve fitting – parameter estimation  

Latest news

  • Fall 2010 BMED360 will have 10 ECTS from Fall 2010The time schedule will be:Lectures on programming labs / demos:Mondays 08:15-16:00 (on 18.10.2010, 08.11.2010 ...
    Posted Jun 16, 2010, 2:08 AM by Arvid Lundervold

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