ISMRM SCIENTIFIC WORKSHOP ~ 3-6 February 2013
 

Data Sampling & Image Reconstruction
 Sedona, AZ, USA
 

OVERVIEW
This data sampling workshop in Sedona is the third installment of the series (after 2007 and 2009), updated to reflect new trends in MRI, keeping many of the successful elements of the last workshops. This workshop will explore the practical boundaries of new and unconventional methods for collecting data (pulse sequences), and for reconstructing images from that data. An emphasis will be placed on reproducible research, exploring ways in which we can work to move our field and our work.

In addition to invited scientific presentations, the program will include proffered talks and poster presentations. A special feature of this workshop will be a new “Recon Challenge”, allowing registrants to both collect data and reconstruct images under particular constraints. As before, the submitted images will be reviewed by a panel of physicians who will lead a discussion on what is needed to produce a “good” image.

The conference will provide a great deal of time for small-group interaction in addition to the very informative and engaging sessions that are planned.
 

TARGET AUDIENCE
The audience will consist primarily of engineers, scientists and clinicians who have an interest in understanding, implementing and refining data collection and reconstruction methods in MRI. These will include people with a good understanding of MRI (e.g. the basics of k-space, eddy currents, motion artifacts), and some familiarity with non-Cartesian (e.g. spiral) trajectories for data collection and methods for reconstruction of images from undersampled data. Participants will come from both academic and industrial settings, as well as governmental and non-governmental research organizations.
 

EDUCATIONAL OBJECTIVES
Upon completion of this activity, participants will be able to:
  • Discuss common methods for collecting and reconstructing non-uniformly sampled data;
  • Describe the advantages that may be obtained through the use of model-based reconstruction methods;
  • Define the underlying principles of constrained reconstruction in MRI; and
  • Describe applications which benefit from new collection and reconstruction methods.