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Improving Cerebral Neural Tract Identification via Fiber Clustering with a Reliable Fiber Similarity Metric 期刊论文

编号：

05f63266-3d91-44b2-81a2-62c189883439
作者：

Yao, Xufeng^[1,2];Wang, Yongxiong^[2];Yu, Tonggang(于同刚)^[3]Zhuang, Songlin^[2];
语种：

English
期刊：

JOURNAL OF MEDICAL IMAGING AND HEALTH INFORMATICS ISSN：2156-7018 2017 年 7 卷 1 期 (241 - 246) ; FEB
收录：
关键词：

Diffusion Tensor Imaging Fiber Clustering,aged Distance Fiber Similarity Metric
摘要：

Fiber clustering has been used to improve the configuration of neuronal fiber tracts in white matter by labeling erroneous fibers in the tract. In this study, we propose a robust differential distance fiber similarity metric as the key component in accurate FC. Compared with the commonly used averaged distance fiber similarity metric, our defined differential distance fiber similarity metric measures differential distances instead of averaged distances between point pairs along two fibers within a tract. To validate the performance of our proposed approach, it was compared with the averaged distance fiber similarity metric on simulated fiber tracts and human data. The results showed that our FC method was superior to the averaged distance fiber similarity metric at correctly labeling the fibers in an individual tract.
推荐引用方式
GB/T 7714：

Yao Xufeng,Wang Yongxiong,Yu Tonggang, et al. Improving Cerebral Neural Tract Identification via Fiber Clustering with a Reliable Fiber Similarity Metric [J].JOURNAL OF MEDICAL IMAGING AND HEALTH INFORMATICS,2017,7(1):241-246.
APA：

Yao Xufeng,Wang Yongxiong,Yu Tonggang,Zhuang Songlin.(2017).Improving Cerebral Neural Tract Identification via Fiber Clustering with a Reliable Fiber Similarity Metric .JOURNAL OF MEDICAL IMAGING AND HEALTH INFORMATICS,7(1):241-246.
MLA：

Yao Xufeng, et al. "Improving Cerebral Neural Tract Identification via Fiber Clustering with a Reliable Fiber Similarity Metric" .JOURNAL OF MEDICAL IMAGING AND HEALTH INFORMATICS 7,1(2017):241-246.

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