CASIA OpenIR  > 脑图谱与类脑智能实验室  > 脑网络组研究
A Bayesian approach to fiber orientation estimation guided by volumetric tract segmentation
Ye, Chuyang1,2; Prince, Jerry L.2
发表期刊COMPUTERIZED MEDICAL IMAGING AND GRAPHICS
2016-12-01
卷号54期号:in press页码:35-47
文章类型Article
摘要Diffusion magnetic resonance imaging (dMRI) provides information about the microstructure of white matter in the human brain. From dMRI, streamlining tractography is often used to reconstruct computational representations of white matter tracts from which differences in structural connectivity can be explored. In the fiber tracking process, anatomical information can help reduce tracking errors caused by crossing fibers and image noise. In this paper, we propose a Bayesian method for estimating fiber orientations (FOs) guided by anatomical tract information using diffusion tensor imaging (DTI), which is a standard clinical and research dMRI protocol. The proposed method is named Fiber Orientation Reconstruction guided by Tract Segmentation (FORTS). A first step segments and labels the white matter tracts volumetrically, including explicit representations of crossing regions. A second step estimates the FOs using the diffusion information and the anatomical knowledge from segmented white matter tracts. A single FO is estimated in the noncrossing regions while two FOs are estimated in the crossing regions. A third step carries out streamlining tractography that uses information from both the segmented tracts and the estimated FOs. Experiments performed on a digital crossing phantom, a physical phantom, and brain DTI of 18 healthy subjects show that FORTS is able to use the anatomical information to produce FOs with better accuracy and to reduce anatomically incorrect streamlines. In particular, on the brain DTI data, we studied the connectivity of anatomically defined tracts to cortical areas, which is not straightforwardly achievable using only volumetric tract segmentation. These connectivity results demonstrate the potential application of FORTS to scientific studies. (C) 2016 Elsevier Ltd. All rights reserved.
关键词Dti Fiber Orientation Estimation Volumetric Tract Segmentation
WOS标题词Science & Technology ; Technology ; Life Sciences & Biomedicine
DOI10.1016/j.compmedimag.2016.09.003
关键词[WOS]GRADIENT VECTOR FLOW ; DTI TRACTOGRAPHY ; CROSSING FIBERS ; DIFFUSION MRI ; RESOLUTION ; BRAIN ; CONNECTIVITY ; DISEASE ; VALIDATION ; INTEGRITY
收录类别SCI
语种英语
项目资助者NIH/NINDS(5R01NS056307 ; China Scholarship Council ; 1R21NS082891)
WOS研究方向Engineering ; Radiology, Nuclear Medicine & Medical Imaging
WOS类目Engineering, Biomedical ; Radiology, Nuclear Medicine & Medical Imaging
WOS记录号WOS:000390513400005
引用统计
被引频次:2[WOS]   [WOS记录]     [WOS相关记录]
文献类型期刊论文
条目标识符http://ir.ia.ac.cn/handle/173211/12099
专题脑图谱与类脑智能实验室_脑网络组研究
通讯作者Ye, Chuyang
作者单位1.Chinese Acad Sci, Inst Automat, Brainnetome Ctr, Beijing, Peoples R China
2.Johns Hopkins Univ, Dept Elect & Comp Engn, Baltimore, MD 21218 USA
第一作者单位中国科学院自动化研究所
通讯作者单位中国科学院自动化研究所
推荐引用方式
GB/T 7714
Ye, Chuyang,Prince, Jerry L.. A Bayesian approach to fiber orientation estimation guided by volumetric tract segmentation[J]. COMPUTERIZED MEDICAL IMAGING AND GRAPHICS,2016,54(in press):35-47.
APA Ye, Chuyang,&Prince, Jerry L..(2016).A Bayesian approach to fiber orientation estimation guided by volumetric tract segmentation.COMPUTERIZED MEDICAL IMAGING AND GRAPHICS,54(in press),35-47.
MLA Ye, Chuyang,et al."A Bayesian approach to fiber orientation estimation guided by volumetric tract segmentation".COMPUTERIZED MEDICAL IMAGING AND GRAPHICS 54.in press(2016):35-47.
条目包含的文件 下载所有文件
文件名称/大小 文献类型 版本类型 开放类型 使用许可
CMIG2.pdf(5693KB)期刊论文作者接受稿开放获取CC BY-NC-SA浏览 下载
个性服务
推荐该条目
保存到收藏夹
查看访问统计
导出为Endnote文件
谷歌学术
谷歌学术中相似的文章
[Ye, Chuyang]的文章
[Prince, Jerry L.]的文章
百度学术
百度学术中相似的文章
[Ye, Chuyang]的文章
[Prince, Jerry L.]的文章
必应学术
必应学术中相似的文章
[Ye, Chuyang]的文章
[Prince, Jerry L.]的文章
相关权益政策
暂无数据
收藏/分享
文件名: CMIG2.pdf
格式: Adobe PDF
此文件暂不支持浏览
所有评论 (0)
暂无评论
 

除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。