Tuesday, March 5

MS19
Image Reconstruction

3:00 PM - 5:00 PM
Room: St. James Room

An important problem in image processing is to reconstruct an image from measured data. Image reconstruction problems arise in many applications, such as medical imaging and nondestructive testing of materials. Advances in technology continually result in new imaging devices, and there is an ncessant desire to reconstruct images with ever higher resolution. As a result, a substantial amount of research is currently being done on many aspects of image reconstruction problems. The talks in this minisymposium report on some new activities related to the mathematical and computational challenges of image reconstruction.

Organizer: Curtis R. Vogel
Montana State University
James G. Nagy
Emory University

3:00-3:25 What Can We Learn About a Continuous Object From Discrete Data?

Harrison H. Barrett, University of Arizona

3:30-3:55 Tomographic Image Reconstruction using the Nonuniform FFT

Bradley Sutton and Jeffrey Fessler, University of Michigan, Ann Arbor

4:00-4:25 Uncertainties in Tomographic Reconstructions Based on Deformable Models

Kenneth M. Hanson, Los Alamos National Laboratory

4:30-4:55 Joint Image Reconstruction and System Identification

Rick Paxman and Brian Thelen, Veridian/ERIM-International