ACM Home Page
Please provide us with feedback. Feedback
Digital Library logoTake a look at the new version of this page: [ beta version ]. Tell us what you think.
Visualization of neuronal fiber connections from DT-MRI with global optimization
Full text PdfPdf (488 KB)
Source Symposium on Applied Computing archive
Proceedings of the 2005 ACM symposium on Applied computing table of contents
Santa Fe, New Mexico
SESSION: Multimedia and visualization (MV) table of contents
Pages: 1200 - 1206  
Year of Publication: 2005
ISBN:1-58113-964-0
Authors
Nathaniel Fout  The University of California, Davis, CA
Jian Huang  The University of Tennessee, Knoxville, TN
Zhaohua Ding  Vanderbilt University, Nashville, TN
Sponsor
SIGAPP: ACM Special Interest Group on Applied Computing
Publisher
ACM  New York, NY, USA
Bibliometrics
Downloads (6 Weeks): 3,   Downloads (12 Months): 47,   Citation Count: 0
Additional Information:

abstract   references   index terms   collaborative colleagues  

Tools and Actions: Request Permissions Request Permissions    Review this Article  
DOI Bookmark: Use this link to bookmark this Article: http://doi.acm.org/10.1145/1066677.1066949
What is a DOI?

ABSTRACT

Diffusion Tensor MRI (DT-MRI) provides valuable 3D data describing diffusion characteristics of water molecules in the human brain. From DT-MRI, it is hoped that neuronal fiber connections among cortical regions can be reliably extracted and adequately interpreted. To achieve this goal, several significant challenges persist. In this paper, by means of dynamic programming we have developed a global fiber reconstruction algorithm enabling efficient visualization of neuronal connections queried by both the start and end points on the fly. Besides an inherent ability to handle noisy datasets, our algorithm also naturally addresses situations where neuronal fibers branch or cross each other. We demonstrate the efficacy of our approach with visualization of neuronal connections among activated brain cortical regions detected by functional MRI (fMRI).


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
1
Mori, S. and van Zijl, P. Fiber Tracking: Principles and Strategies - A Technical Review. NMR Biomed, 2002. 15 (468--480).
 
2
 
3
 
4
Basser, P. J., Pajevic, S., Pierpaoli, C., Duda, J., Aldroubi, A. In vivo fiber tractography using DT-MRI Data. Magn Reson Med, 2000. 44(625--632).
 
5
Poupon, C., Clark, C. A., Frouin, V., Regis, J., Bloch, L., Le Bihan, D., Mangin, J. F. Regularization of diffusion-based direction maps for the tracking of brain white matter fascicles. NeuroImage, 2000. 12: p. 184--195.
 
6
 
7
Parker, G. J. Tracing fiber tracts using fast marching.In Proceedings, International Society of Magnetic Resonance. 2000. Denver, CO.
 
8
Tuch, D. S., Wiegell, M. R., Reese, T. G., Belliveau, J. W., Wedeen, V. Measuring cortico-corital connectivity matrices with diffusion spectrum imaging. In Proceedings of International Society of Magnetic Resonance. 2001. Glasgow, UK.
 
9
Bjornemo, M., Brun, A., Kikinis, R., Westin, C. F. Regularized Stochastic White Matter Tractography Using Diffusion Tensor MRI. 2002.

Collaborative Colleagues:
Nathaniel Fout: colleagues
Jian Huang: colleagues
Zhaohua Ding: colleagues