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
Sara Rolfe, RA
Brinkley
Indriyati Atmosukarto, RA
 Jia Wu, RA
 Lynn Yang, RA
Kasia Wilamowska, RA
atmosukarto


Collaborators:

Ravensara Travillian
 John Clark
 Michael Cunningham
 Carrie Heike
 Rosalia Tungaraza




Eye and Skull Shape Demos

Publications:

  • I. Atmosukarto, L. G. Shapiro, J. R. Starr, C. L. Heike, B. Collett, M. L. Cunningham, M. L. Speltz, "3D Head Shape Quantification for Infants with and without Deformational Plagiocephaly", The Cleft-Palate Craniofacial Journal, 2009.
  • I. Atmosukarto, K. Wilamowska, C. Heike, L. G. Shapiro. "3D Object Classification using Salient Point Patterns With Application to Craniofacial Research,Pattern Recognition, 2009.
  • I. Atmosukarto and L. G. Shapiro, "3D Object Retrieval Using Salient Views", ACM Multimedia Information Retrieval, 2010.
  • R. F. Tungaraza, J. Guan, L. G. Shapiro, J. F. Brinkley, J. Ojemann, and J. D. Franklin, "A Similarity Retrieval Tool for Functional Magnetic Resonance Imaging (fMRI) Statistical Maps," Artificial Intelligence in Medicine, to appear 2009.
  • R. F. Tungaraza, J. Guan, S. Rolfe, I. Atmosukarto, A. Poliakov, N. M. Kleinhans, E. Aylward, J. Ojemann, J. F. Brinkley, L. G. Shapiro, "A Similarity Retrieval Method for Functional Magnetic Resonance Imaging (fMRI) Statistical Maps," SPIE Medical Imaging: Image Processing, 2009.
  • L Shapiro, K Wilamowska, I Atmosukarto, J Wu, CL Heike, M Spelz, and M Cunningham. "Shape-Based Classification of 3D Head Data." International Conference on Image Analysis and Processing, 2009.
  • K Wilamowska, L Shapiro, and CL Heike. "Quantification of 3D face shape in 22q11.2 deletion syndrome". IEEE International Symposium on Biomedical Imaging, 2009.
  • S. M. Rolfe, L. Finney, R. F. Tungaraza, J. Guan, L.G. Shapiro, J.F. Brinkely, A. Poliakov, N. Kleinhans, E. Alyward, "An independent component analysis based tool for exploring functional connections in the brain," SPIE Medical Imaging: Image Processing, 2009.
  • I. Atmosukarto, L. Shapiro, M. Cunningham, and M. Speltz. "Automatic 3D Shape Severity Quantification and Localization for Deformational Plagiocephaly".  In Proc. SPIE Medical Imaging: Image Processing, 2009.
  • S.Yang, I. Atmosukarto, J. Franklin, J. F. Brinkley, D. Suciu, and L. G. Shapiro,"A Model of Multimodal Fusion for Medical Applications," SPIE Multimedia Content Access: Algorithms and Systems III, 2009.
  • J-H. Chen and L. G. Shapiro, "Medical image segmentation via min s-t cuts with sides constraints", ICPR, 2008.
  • I. Atmosukarto and L. G. Shapiro, " A Learning Approach to 3D Object Classification", S+SSPR, 2008.
  • I. Atmosukarto and L. G.Shapiro, "A Salient-Point  Signature for 3D Object Retrieval", ACM Multimedia Information Retrieval, 2008.
  • 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.