Novel Indexing and Retrieval of Dynamic Brain Images

Publications

1. [PDF] Bai B, Kantor P, Shokoufandeh A. Effectiveness of the Finite Impulse Response model in content based fMRI image retrieval. To appear in MICCAI 2007.

2. [PDF] Bai B, Kantor P, Shokoufandeh A, Silver D. fMRI Brain Image Retrieval Based on ICA Components. To appear in ENC 2007.

3. [PDF] Bai B, Kantor P, Silver D, Cornea N. Toward content-based indexing and retrieval of brain images. In the proceedings of RIAO 2007.

4. [PDF] Bai B, Kantor P. A shape-based Finite Impulse Response (FIR) model for functional brain image. In the Proceedings of the 4^th IEEE International Symposium of Biomedical Imaging (ISBI) 2007.

5. [PDF] Bai B, Kantor P, Silver D, Cornea N. IR principles for content-based indexing and retrieval of brain images. In the Proceedings of the 15^th ACM Internal Conference on Information and Knowledge Management (CIKM) 2006.

6. [PDF] Cornea ND, Demirci MF, Silver D, Shokoufandeh A, Dickinson SJ, Kantor PB. 3D Object Retrieval using Many-to-many Matching of Curve Skeletons. IEEE International Conference on Shape Modeling and Applications (SMI 2005), pp. 368-373, MIT, Boston, MA. June 15-17, 2005.

7. [PDF] Bai B, Feature extraction and matching in content-based retrieval of functional Magnetic Resonance Images. Ph.D thesis. Rutgers University. 2007.

8. [DOC] Cornea ND, Curve-skeletons of 3D objects: algorithms and applications. Ph.D thesis. Rutgers University. 2007.

9. [PDF] Ibraev U, Imposing Graph Structures on Space-Time Densities for Indexing and Retrieval. Ph.D thesis. Rutgers University. 2005.

Under Review

10. [PDF] Novatnak J, Cornea N, Shokoufandeh A, Dickinson S, Silver D, Kantor P, Bai B. A Generalized Family of Fixed-Radius Distribution-Based Distance Measures for Comparing fMRI. under review.

11. [PDF] Bai B, Cornea N, Ibraev U, Shokoufandeh A, Silver D, Dickinson S, Kantor P. A New Paradigm for Data-Sharing on Brain Function, in preparation.

The goal of this project is to support a new kind of “Query by Example” access to archives of space-time brain images (fMRI), usable by clinicians and researchers for research and diagnosis.

Brain imaging archives have been limited to non-image based metadata, which omit critical issues of spatial localization and temporal dynamics. In the proposed archival model, such metadata will complement the algorithmic indexing of dynamic brain images, supporting the discovery of unexpected functional relationships and brain processes. This project will help to make neuroimaging analysis tools available to clinical and industrial investigators who are best positioned to adapt new methods to applied domains.

This project is a collaboration between Rutgers/Drexel/Toronto.

Brain Imaging Research Group Occasional Seminar

Research Topics:

	Indexing of brain images using B2COS metric
	Indexing using other metrics
	3D Shape Matching
	Earth Mover's Distance
	Canonical Sets
	CCVT --- Cluster Comparison and Visualization Tool. A visualization tool for interactive exploration of processed fMRI data.

Personnel

Faculty:

Dickinson, Sven

Kantor, Paul, Project Director

Students:

Collaboratory web site for on-line Notebooks (password protected): LinksToSites.html

Posters

Several poster slides are available, reflecting work in progress

Future Work
We have planned a great deal of follow-on work, which is summarized in an extract from one recently submitted proposal to the National Science Foundation.

A web site for the RUMBA software component of the project is found at: RUMBA

Acknowledgment: "This material is based upon work supported by the National Science Foundation under Grant No. ITR 0205178." "Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation."