Fast and accurate connectivity analysis between functional regions based on DT-MRI

Authors:
Dorit Merhof;Mirco Richter;Frank Enders;Peter Hastreiter;Oliver Ganslandt;Michael Buchfelder;Christopher Nimsky;Günther Greiner
Affiliations:
Computer Graphics Group, University of Erlangen-Nuremberg, Germany;Computer Graphics Group, University of Erlangen-Nuremberg, Germany;Computer Graphics Group, University of Erlangen-Nuremberg, Germany;Computer Graphics Group, University of Erlangen-Nuremberg, Germany;Neurocenter, Dept. of Neurosurgery, University of Erlangen-Nuremberg, Germany;Neurocenter, Dept. of Neurosurgery, University of Erlangen-Nuremberg, Germany;Neurocenter, Dept. of Neurosurgery, University of Erlangen-Nuremberg, Germany;Computer Graphics Group, University of Erlangen-Nuremberg, Germany
Venue:
MICCAI'06 Proceedings of the 9th international conference on Medical Image Computing and Computer-Assisted Intervention - Volume Part II
Year:
2006

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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.