On the Accuracy of Fiber Tractography

  • Invasive neurosurgical interventions bear the risk of damaging indispensable fiber pathways. Current fiber reconstruction techniques based on diffusion tensor imaging (DTI) do not determine the spatial extent of a fiber bundle in an accurate and reliable manner, due to errors and imprecisions in both the imaging and the algorithmic pipeline. In this thesis, we start by quantifying the errors of current fiber tracking algorithms by means of novel software phantoms which provide a realistic model of neural fiber bundles. This knowledge is used to locally analyze the quality of a patient's diffusion tensor dataset and to construct individual confidence hulls around the tracked fibers. In the following chapter, these ideas are developed further and we suggest an accurate approach to the segmentation of a patient's diffusion tensor image which combines connectivity and tensor clustering information. We then focus our attention on the sensitivity of streamline tractography to user-defined regions of interest. In order to reduce this sensitivity, we demonstrate the feasibility of mapping a fiber bundle from a fiber atlas onto the DTI dataset of a patient. In the last chapter of this thesis, we consider several alternatives to visualize fiber-tracking related uncertainties by means of color-coded streamlines and confidence hulls.

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Publishing Institution:IRC-Library, Information Resource Center der Jacobs University Bremen
Granting Institution:Jacobs Univ.
Author:Sebastiano Barbieri
Referee:Horst Hahn, Andreas Nüchter, Anna Vilanova i Bartroli
Advisor:Horst Hahn
Persistent Identifier (URN):urn:nbn:de:101:1-201307119339
Document Type:PhD Thesis
Language:English
Date of Successful Oral Defense:2012/09/24
Year of Completion:2012
Date of First Publication:2013/02/20
PhD Degree:Computer Science
School:SES School of Engineering and Science
Other Organisations Involved:Fraunhofer MEVIS
Library of Congress Classification:R Medicine / R Medicine (General) / R858-859.7 Computer applications to medicine. Medical informatics
Call No:Thesis 2012/54

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