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Fast and Accurate Connectivity Analysis Between Functional Regions Based on DT-MRI

  • Dorit Merhof
  • Mirco Richter
  • Frank Enders
  • Peter Hastreiter
  • Oliver Ganslandt
  • Michael Buchfelder
  • Christopher Nimsky
  • Günther Greiner
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4191)

Abstract

Diffusion tensor and functional MRI data provide insight into function and structure of the human brain. However, connectivity analysis between functional areas is still a challenge when using traditional fiber tracking techniques. For this reason, alternative approaches incorporating the entire tensor information have emerged. Based on previous research employing pathfinding for connectivity analysis, we present a novel search grid and an improved cost function which essentially contributes to more precise paths. Additionally, implementation aspects are considered making connectivity analysis very efficient which is crucial for surgery planning. In comparison to other algorithms, the presented technique is by far faster while providing connections of comparable quality. The clinical relevance is demonstrated by reconstructed connections between motor and sensory speech areas in patients with lesions located in between.

Keywords

Cost Function Fractional Anisotropy Diffusion Tensor Imaging Diffusion Tensor Connectivity Analysis 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Dorit Merhof
    • 1
    • 2
  • Mirco Richter
    • 1
  • Frank Enders
    • 1
    • 2
  • Peter Hastreiter
    • 1
    • 2
  • Oliver Ganslandt
    • 2
  • Michael Buchfelder
    • 2
  • Christopher Nimsky
    • 2
  • Günther Greiner
    • 1
  1. 1.Computer Graphics GroupUniversity of Erlangen-NurembergGermany
  2. 2.Neurocenter, Dept. of NeurosurgeryUniversity of Erlangen-NurembergGermany

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