Advances in Diffusion MRI Analysis, tutorial at MICCAI 2010


MICCAI 2009 Diffusion MRI Tutorial:
Trends in High Angular Resolution Diffusion Imaging and Brain Tissue Modeling

The processing and analysis of diffusion weighted imaging data is a task considered to be very challenging due to the complex underlying properties of the data, but is becoming more mature owing to major new research contributions from various fields like physics, mathematics, statistics, computing and visualization. Prompted by its growing contribution to disease investigation, there has been an increased interest in addressing the mathematical and technical issues associated with the analysis of such data, by development of sophisticated techniques for the same - a trend that is evident in recent research. There is also an increase in DWI being added to clinical studies, leading to large amounts of data being acquired, needing analysis. This underlines the crucial need for a common protocol in handling processing, analysis and quality control of data. The tutorial proposes to address the challenging issues of standardization and comparability in different aspects of diffusion imaging: reconstruction, quality analysis of acquired data, registration, statistics/regression and tracking, across different research groups. The talks and the subsequent panel discussion would present the state-of-the-art as well as build towards a "protocol" that can be directly applied, for any/several of these tasks. The focus of our diffusion MRI tutorials at MICCAI 2007, and MICCAI 2008 were mainly on introductory material, and overall these tutorials where quite successful and very well received. To attract some of the same audience this year, we plan to have a focus on more complex diffusion modeling, and include recent developments in tissue modeling from MRI diffusion measurements. More specifically we plan to cover the following material:

Tissue modeling
Modeling the diffusion MRI signal
Experiment Design
Recovering microstructural indices
Fibre crossings and high angular resolution methods
Connectivity mapping
Tract-based analysis and statistics
Inference and classification


Carl-Fredrik Westin, PhD
Director, Laboratory of Mathematics in Imaging (LMI)
Department of Radiology, Harvard Medical School
Brigham and Women's Hospital, Boston

Ragini Verma, PhD
Section of Biomedical Image Analysis, Dept. of Radiology
University of Pennsylvania, Philadelphia

Daniel Alexander, PhD
Reader in Imaging Sciences
Centre for Medical Image Computing
Dept. Computer Science, University College London (UCL), London, UK

Rachid Deriche, PhD
Research Director, INRIA
Odyssee Project Team
INRIA Sophia Antipolis - Mediterranee Research Center. France


Parent: DMRI09 Revision: r65 - 19 Jun 2010 - 06:06:21 - CarlFredrikWestin

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