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Visualization of neuronal fiber connections from DT-MRI with global optimization

Published: 13 March 2005 Publication History

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).

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Cited By

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  • (2022)Deep learning-assisted fully automatic fiber tracking for tremor treatmentMedical Imaging 2022: Image-Guided Procedures, Robotic Interventions, and Modeling10.1117/12.2611710(79)Online publication date: 4-Apr-2022
  • (2013)Cortico-Cortical, Cortico-Striatal, and Cortico-Thalamic White Matter Fiber Tracts Generated in the Macaque Brain via Dynamic ProgrammingBrain Connectivity10.1089/brain.2013.01433:5(475-490)Online publication date: Oct-2013
  • (2010)Discretizing stochastic tractographyProceedings of the 2010 IEEE international conference on Biomedical imaging: from nano to Macro10.5555/1855963.1856315(1381-1384)Online publication date: 14-Apr-2010
  • Show More Cited By

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cover image ACM Conferences
SAC '05: Proceedings of the 2005 ACM symposium on Applied computing
March 2005
1814 pages
ISBN:1581139640
DOI:10.1145/1066677
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

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Publication History

Published: 13 March 2005

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Author Tags

  1. DT-MRI
  2. conditional probability and Bayes rule
  3. dynamic programming
  4. fMRI
  5. fiber tracking
  6. global optimization
  7. reconstruction

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SAC05
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SAC05: The 2005 ACM Symposium on Applied Computing
March 13 - 17, 2005
New Mexico, Santa Fe

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Overall Acceptance Rate 1,650 of 6,669 submissions, 25%

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Cited By

View all
  • (2022)Deep learning-assisted fully automatic fiber tracking for tremor treatmentMedical Imaging 2022: Image-Guided Procedures, Robotic Interventions, and Modeling10.1117/12.2611710(79)Online publication date: 4-Apr-2022
  • (2013)Cortico-Cortical, Cortico-Striatal, and Cortico-Thalamic White Matter Fiber Tracts Generated in the Macaque Brain via Dynamic ProgrammingBrain Connectivity10.1089/brain.2013.01433:5(475-490)Online publication date: Oct-2013
  • (2010)Discretizing stochastic tractographyProceedings of the 2010 IEEE international conference on Biomedical imaging: from nano to Macro10.5555/1855963.1856315(1381-1384)Online publication date: 14-Apr-2010
  • (2010)Discretizing stochastic tractography: A fast implementation2010 IEEE International Symposium on Biomedical Imaging: From Nano to Macro10.1109/ISBI.2010.5490255(1381-1384)Online publication date: Apr-2010
  • (2009)Combinatorial fiber-tracking of the human brainNeuroImage10.1016/j.neuroimage.2009.05.08648:3(532-540)Online publication date: Nov-2009
  • (2007)An image-processing toolset for diffusion tensor tractographyMagnetic Resonance Imaging10.1016/j.mri.2006.10.00625:3(365-376)Online publication date: Apr-2007
  • (2006)Fast and accurate connectivity analysis between functional regions based on DT-MRIProceedings of the 9th international conference on Medical Image Computing and Computer-Assisted Intervention - Volume Part II10.1007/11866763_28(225-233)Online publication date: 1-Oct-2006

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