DE | EN
Home
About Us
Overview
Facts and Figures
Organization
Scientists
Contact
Approach
Situations offered
Research
Overview
Application Fields
Projects
Publications
Scientists
Preprints
Institutional Cooperation
Archiv 02-14
Transfer
Overview
Industry
References
MODAL-AG
Spin Offs
Software
Patents
Schools
Overview
MathInside
MATHEATHLON
Matheon-Kalender
What'sMath
Training for Teachers
Summer Schools
Events
Press
Overview
Releases
News
Overview
Matheon Head
Number of the week
News 2002 - 2014
Activities
Overview
Workshops
15 Years Matheon
Media
Overview
Photos
Videos
Audios
Booklets
Books
News from around the world

Dr. Guozhi Dong

Postdoc researcher at Humboldt University of Berlin

Institute of Mathematics
guozhi.dong@hu-berlin.de


Projects as a member

  • CH12

    Advanced Magnetic Resonance Imaging: Fingerprinting and Geometric Quantification

    Prof. Dr. Michael Hintermüller

    Project heads: Prof. Dr. Michael Hintermüller
    Project members: Dr. Guozhi Dong
    Duration: -
    Status: running
    Located at: Humboldt Universität Berlin

    Description

    Very recently, magnetic resonance fingerprinting (MRF) has been introduced as a highly promising MRI acquisition scheme which allows for the simultaneous quantification of the tissue parameters (e.g. T1, T2 and others) using a single acquisition process. In MRF, the tissue of interest is excited through a random sequence of pulses without needing to wait for the system to return to equilibrium between pulses. After each pulse, a subset of the signal's Fourier coefficients is collected, as in classical MRI, and a reconstruction of the net magnetization image is performed. These reconstructions suffer from the presence of artifacts since the Fourier coefficients are not fully sampled. The formed sequence of image elements is then compared to a family of predicted sequences (dictionary of fingerprints) each of which corresponds to a specific combination of values of the tissue parameters. This dictionary is computed beforehand by solving the Bloch equations. The idea is that, provided the dictionary is rich enough, every material element (voxel) can be then mapped to its parameter values. While first very promising results have been obtained in biomedical engineering, many aspects of MRF remain widely open and require a proper mathematization for optimizing and robustifying the procedure. The aim of this project is, thus, to provide a quantitative mathematical model for the MRF process, leading to a variational image reconstruction problem subject to dynamical constraints describing magnetization and an embedded reconstruction scheme. This model will be subject to a detailed mathematical analysis and its efficient numerical solution.

    http://wias-berlin.de/people/papafitsoros/MRF/

Projects as a guest