Parameter Estimation and geometric fiber reconstruction from Diffusion Tensor Images of the brain.
A BematA Project

Project Description

In this project, mathematical and computational aspects of Diffusion Tensor Magnetic Resonance Imaging (DTMRI) of the human brain are studied. The DTMRI technique enables depictions of diffusion anisotropy and geometric reconstruction of local nerve fiber orientation. Because of the huge amount of data coming from the DTMRI process, effective and reliable methods for processing of the data is crucial. The project will focus on methodological research issues at all steps in the processing chain from data collection to fiber reconstruction. We restrict the study to data from healthy volunteers.

Contact Persons

Professor Xue-Cheng Tai, University of Bergen, Department of Mathematics; tai@mi.uib.no
Associate Professor Arvid Lundervold, University of Bergen, Section on Neuroscience; arvid.lundervold@biomed.uib.no
Professor Tai acts as the administrative coordinator of the project and is responsible for the correspondence with the Research Council.

Sponsor

This project is supported by The Research Council of Norway (Norges forskningsråd) under project BeMatA.

Candidates

The following candidate is taken up for the position in connection with this project.
Johan Lie johanl@mi.uib.no The main supervisor of this project is Prof. Xue-Cheng Tai.

Publications 

  1. K. Majava and X.-C. Tai,
    A Level Set Method for Solving Free Boundary Problems Associated with Obstacles, International J. Numer. Anal. Modelling, vol. 1, no.2,  pp.157-172, 2004. (Also as UCLA,  Applied Mathematics, CAM-report-03-69, November 2003.)   Download pdf file

  2. Xue-Cheng Tai and Tony F. Chan,
    A survey on Multiple Level Set Methods with Applications for Identifying Piecewise Constant Functions, International J. Numer. Anal. Modelling, vol. 1, no.1,  pp.25-48, 2004.  (Also as  UCLA,  Applied Mathematics, CAM-report-03-68, November 2003.)  Download pdf file
     
  3. Marius Lysaker, Stanley Osher, Xue-Cheng Tai,
    Noise Removal Using Smoothed Normals and Surface Fitting, January 2003.  Accepted and to appear in  IEEE Transection on image processing.  (Also UCLA,  Applied Mathematics, CAM-report-03-03.)

  4.  Johan Lie, Marius Lysaker and  Xue-Cheng Tai,
     A Variant of the Level Set Method and Applications to Image Segmentation, September 2003.   UCLA,  Applied Mathematics, CAM-report-03-50.

  5. Johan Lie, Marius Lysaker and Xue-Cheng Tai, A Binary Level Set Model and Some Applications to Mumford-Shah Image Segmentation, May 2004, UCLA,  Applied Mathematics, CAM-report-04-31.

  6. Johan Lie. Variational image segmentation using discontinuous level set formulations. Master's thesis, 2003.
    [ bib | .pdf ]