Advanced Topics in Analysis of Structural and Functional MRI Data

Organizers: Vincent D. Calhoun, Ph.D. and Mark Jenkinson, Ph.D.
Skill level:  Advanced

Saturday, 3 May 2008


The aim of this one-day course is to discuss intermediate to advanced level techniques for quantitative imaging and data analysis and post-processing of images and data, including artifact-correction at both the acquisition and post-acquisition phase; parameter estimation using Baysian analysis methods; segmentation and atlas construction; cardiac motion correction, GLM-based artifact correction for fMRI, multi-modal data analysis; and an introduction to general multi-variate and data-driven analysis techniques. Applications of the methods will be demonstrated in a range of body areas.

Educational Objectives:

Upon completion of this course, participants should be able to:

  • Describe the methods used for acquisition of quantitative MR parameters, how these are affected by artifacts and techniques for optimizing acquisitions;
  • Identify sources of image/data artifact, be able to apply methods for artifact reduction in post-processing and understand their limitations;
  • Describe the principles of Bayesian data analysis and how it is applied to parameter estimation;
  • Explain how different segmentation and atlas construction methods work and how the different atlases can be used;
  • Describe and contrast multi-variate methods for analysis and explain how these can be used as data-driven analysis techniques;
  • Explain the motivation and some approaches for combining multi-modal data.
  • Audience Description:

    This course is designed for individuals with some familiarity in data analysis (such as gained from attending the introductory course on Quantitative Imaging and Data Analysis at last year's meeting) and with a sound grasp of mathematics and the basic science of MRI.

    The content is suitable for either clinical or basic science researchers who have some experience in analyzing  MR data or designing methods for acquiring accurate quantitative data.

    This course is especially suitable for students who wish to build upon a basic foundation in data analysis methods for MR, as well as for application-oriented researchers who wish to understand and apply cutting-edge methods of imaging and analysis to their problems.

      Structural, Quantitative and Cardiac MRI  
    9:00 Optimizing Acquisition of Quantitative Data Gareth J. Barker, Ph.D.
    9:45 Structural Artifact Correction William Wells, Ph.D.
    10:30 Break  
    10:30 - 10:45 Meet the Teachers  
    10:50 Morphometric Analysis: Registration, Segmentation & Atlases Sarong Joshi
    11:35 Cardiac Motion Correction and Tracking Jerry L. Prince, Ph.D.
    12:20 Break  
    12:20 - 12:35 Meet the Teachers  
      Functional MRI  
    13:45 Multi-modal Data Analysis (EEG/FMRI/DWI) Hae-Jeong Park, Ph.D.
    14:30 Bayesian Analysis and Estimation Michael Chappell, Ph.D.
    15:15 Break  
    15:15 - 15:30 Meet the Teachers  
    15:45 Functional Artifact Correction Terry Oakes, Ph.D.
    16:30 Multi-variate and Data-driven Analysis Tulay Adali, Ph.D.
    17:15 Pattern Classification: SVM and Related Techniques James Haxby, Ph.D
    18:00 Adjournment  
    18:00 - 18:15 Meet the Teachers