CNLS - X-Division - LANL

Workshop on

Image Analysis and Understanding Data
 From Scientific Experiments

DECEMBER 2-6, 2002

LOS ALAMOS NATIONAL LABORATORY
LOS ALAMOS, NEW MEXICO  USA

Invited Speakers:  (click name to view web site)

Jonas August -- Carnegie Mellon Univ.
Andrea Bertozzi -- Duke Univ.
Chris Borel -- Los Alamos National Lab.
Yoram Bresler -- Univ. of Illinois-Champaign Urbana
Tony Chan -- Univ. of California - LA
Jeff Fessler -- Univ. of Michigan
W. Clem Karl -- Boston Univ.
Richard Leahy -- Univ. of Southern California
Peyman Milanfar -- Univ. of California - SC
Michael Miller -- Johns Hopkins Univ.
Stan Osher-- Univ. of California - LA
Marios Pattichis -- Univ. of New Mexico
Tilak Ratnanather -- Johns Hopkins Univ.
Guillermo Sapiro -- Univ. of Minnesota
Jackie Shen -- Univ. of Minnesota
Gil Strang -- Massachusetts Institute of Technology
James Theiler -- Los Alamos National Lab.
Richard Tsai -- Princeton Univ.
Luminita Vese -- Univ. of California - LA
David Wilson -- Univ. of Florida
Alan Yuille -- Univ. of California - LA
Song-Chun Zhu -- Univ. of California - LA

Organizing Committee: (click name to send email)

Kevin R. Vixie (Chairman)
Marian Anghel
Thomas J. Asaki
Andrew Fraser
Nick Hengartner
Pieter J. Swart
James Theiler
Brendt E. Wohlberg

For Further Information Contact:

Rod Garcia
Conference Coordinator
Center for Nonlinear Studies
MS: B258
Los Alamos National Lab.
Los Alamos, NM 87545
(505) 667-1444
(505) 665-2659 Fax
ragarcia@lanl.gov

The main focus of the workshop will be the analysis of image or image-like data with a view to the rigorous analysis of data from scientific experiments.  Image data derived from the measurement of scientific experiments present important challenges to the analysis of those images due to demands which are typically more stringent than those made when the end user of the image analysis is the human eye (i.e. when the final "metric" is the infamous viewgraph norm). Tasks such as the construction of image metrics based on the underlying physical of biological process, modeling of the noise processes and their interaction with the process being measured, and restoration of degraded images to be used for parameter estimation of underlying physical parameters are just three examples of task which are very important to the process of rigorous, quantified analysis of data from experiments and the comparison to theory and/or computation.  Because the analysis of non-image high-dimensional data often has very large overlap with the analysis of scientific image data, contributions along these lines are also welcome. 

Two days of short courses are being planned to follow the workshop.

View workshop background document (PDF) Click Here