Department of Computer Science and
Engineering
University of Washington
Multimedia Information Retrieval for Biological Applications
This research is supported by the National Science Foundation under
grant number DBI-0543631. Any opinions, findings and conclusions or
recommendations expressed in this material are those of the authors and
do not necessarly reflect the views of the National Science Foundation.
Project Summary:
Scientific research in the biological domain generates massive amounts
of data of many different kinds. With a hypothesis to investigate,
researchers run large numbers of experiments that use data
from human and animal subjects and produce multiple outputs of
different modalities ranging from simple textual data, to signal,
image, and 3D volumes such as CT and MRI scans.In spite of the massive
scale and complexity, many researchers at the forefront of biological
sciences are using antiquated methods for storing their multimedia
data. Data are often kept in multiple locations including computers,
notebooks, and file drawers.
The goal of this research is to develop a unified methodology for
organization and retrieval of biological data from scientific
experiments. Our work builds on existing work in experiment
management, approximate queries, and content-based image retrieval. We
are developing a query framework for multimedia data that provides
users with a unified way to access multiple types of
data. Queries will be able to handle both single data types and
multiple related data types, such as registered CT and MRI scans or
neuronal firing patterns and related fMRI data. The data will
be organized in a way that is both easy for users to understand and
efficient query access. A prototype system will be built and evaluated
on thee different applications: a study of language sites in the human
brain, an analysis of the relationship of cataract formation to genetic
factors, and a study of craniofacial disorders in children.
People:
Linda Shapiro, PI
|
James Brinkley, co-PI
|
Dan Suciu, co-PI
|
Joshua Franklin, Staff Programmer
|
 |
|
 |
 |
Indriyati Atmosukarto, RA
|
Rosalia Tungaraza, RA
|
Lynn Yang, RA
|
Kasia Wilamowska, NSF Fellow
|
|
|
|
|
Collaborators:
Ravensara Travillian
|
John Clark
|
Michael Cunningham
|
Carrie Heike
|
Sara Rolfe
|
 |
|
|
|
 |
Publications:
- I. Atmosukarto, R. Travillian,
J. Franklin, L. Shapiro, J. Brinkley, D. Suciu, J. Clark, M.
Cunningham. A Unifying
Framework for
Combining Content-Based Image Retrieval with Relational Database
Queries for
Biomedical Applications. Annual
Meeting of the Society for Imaging Informatics in Medicine, 2008.
- L. G. Shapiro, I. Atmosukarto, H. Cho,
H. J. Lin, S. Ruiz-Correa, and J. Yuen. Similarity-Based Retrieval for
Biomedical Applications. Case-Based
Reasoning on Signals and Images. P. Perner (Ed.), Springer, 2007.
- S. Rolfe, An Independent
Component
Analysis Tool for Exploring Functional Connections in the Brain,
MS Thesis, Electrical Engineering Department, University of Washington,
June, 2007.