Automatic Removal of False Connections in Diffusion MRI Tractography Using Topology-Informed Pruning (TIP)

被引:0
|
作者
Fang-Cheng Yeh
Sandip Panesar
Jessica Barrios
David Fernandes
Kumar Abhinav
Antonio Meola
Juan C. Fernandez-Miranda
机构
[1] University of Pittsburgh Medical Center,Department of Neurological Surgery
[2] University of Pittsburgh Medical Center,Department of Bioengineering
[3] Stanford University School of Medicine,Department of Neurosurgery
来源
Neurotherapeutics | 2019年 / 16卷
关键词
Deterministic fiber tracking; Tractography; Topology; Structural connectome; Diffusion MRI;
D O I
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学科分类号
摘要
Diffusion MRI fiber tracking provides a non-invasive method for mapping the trajectories of human brain connections, but its false connection problem has been a major challenge. This study introduces topology-informed pruning (TIP), a method that automatically identifies singular tracts and eliminates them to improve the tracking accuracy. The accuracy of the tractography with and without TIP was evaluated by a team of 6 neuroanatomists in a blinded setting to examine whether TIP could improve the accuracy. The results showed that TIP improved the tracking accuracy by 11.93% in the single-shell scheme and by 3.47% in the grid scheme. The improvement is significantly different from a random pruning (p value < 0.001). The diagnostic agreement between TIP and neuroanatomists was comparable to the agreement between neuroanatomists. The proposed TIP algorithm can be used to automatically clean-up noisy fibers in deterministic tractography, with a potential to confirm the existence of a fiber connection in basic neuroanatomical studies or clinical neurosurgical planning.
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页码:52 / 58
页数:6
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