Fast and accurate connectivity analysis between functional regions based on DT-MRI.
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.
Merhof
Dorit
D
Computer Graphics Group, University of Erlangen-Nuremberg, Germany. merhof@cs.fau.de
Richter
Mirco
M
Enders
Frank
F
Hastreiter
Peter
P
Ganslandt
Oliver
O
Buchfelder
Michael
M
Nimsky
Christopher
C
Greiner
Günther
G
D000465:Algorithms; D001921:Brain / Q000033:anatomy & histology* / Q000502:physiology*; D001931:Brain Mapping / Q000379:methods*; D038524:Diffusion Magnetic Resonance Imaging / Q000379:methods*; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D009434:Neural Pathways / Q000033:anatomy & histology* / Q000502:physiology*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity