Fiber tracking from DTI using linear state space models: Detectability of the 
pyramidal tract

Gössl, C; Fahrmeir, L; Pütz, B; Auer, LM; Auer, DP

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Fiber tracking from DTI using linear state space models: Detectability of the pyramidal tract

Gössl, C., Fahrmeir, L., Pütz, B., Auer, L., & Auer, D. (2002). Fiber tracking from DTI using linear state space models: Detectability of the pyramidal tract. NeuroImage, 16(2), 378-388.

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Item Permalink: https://hdl.handle.net/11858/00-001M-0000-000E-A1DF-C Version Permalink: https://hdl.handle.net/11858/00-001M-0000-000E-A1E0-6

Genre: Journal Article

Alternative Title : Neuroimage

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Creators:
Gössl, C¹, Author
Fahrmeir, L¹, Author
Pütz, B¹, Author
Auer, LM¹, Author
Auer, DP¹, Author

Affiliations:
1Max Planck Institute of Psychiatry, Max Planck Society, ou_1607137

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Free keywords: diffusion tensor imaging; DTI; linear state space models; pyramidal tract; neurosurgical planning

Abstract: Diffusion tensor imaging (DTI) is an emerging and promising tool to provide information about the course of white matter fiber tracts in the human brain. Based on specific acquisition schemes, diffusion tensor data resemble local fiber orientations allowing for a reconstruction of the fiber bundles. Current techniques to calculate fascicles range from simple heuristic tracking solutions to Bayesian and differential equations approaches. Most methods are based only on local diffusion information, often resulting in bending or kinking fiber paths in voxels with reduced diffusion properties. In this article we present a new tracking approach based on linear state space models encompassing an inherent smoothness criterion to avoid too wiggly tracked fiber bundles. The new technique will be described formally and tested on simulated and real data. The performance tests are focused on the pyramidal tract, where we employed a test-retest study and a group comparison in healthy subjects. Anatomical course was confirmed in a patient with selective degeneration of the pyramidal tract. The potential of the presented technique for improved neurosurgical planning is demonstrated by visualization of a tumor-induced displacement of the motor pathways. The paper closes with a thorough discussion of perspectives and limitations of the new tracking approach. (C) 2002 Elsevier Science (USA)

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Language(s): eng - English

Dates: Date issued: 2002-06

Publication Status: Issued

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Rev. Type: Peer

Identifiers: eDoc: 4143
ISI: 000176119300007

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Title: NeuroImage

Alternative Title : Neuroimage

Source Genre: Journal

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Pages: - Volume / Issue: 16 (2) Sequence Number: - Start / End Page: 378 - 388 Identifier: ISSN: 1053-8119