A Bayesian approach to fiber orientation estimation guided by volumetric tract segmentation

doi:10.1016/j.compmedimag.2016.09.003

	A Bayesian approach to fiber orientation estimation guided by volumetric tract segmentation
	Ye, Chuyang1,2 ; Prince, Jerry L.2
刊名	COMPUTERIZED MEDICAL IMAGING AND GRAPHICS
	2016-12-01
卷号	54 期号:in press 页码:35-47
关键词	Dti Fiber Orientation Estimation Volumetric Tract Segmentation
DOI	10.1016/j.compmedimag.2016.09.003
文献子类	Article
英文摘要	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.
WOS关键词	GRADIENT VECTOR FLOW ; DTI TRACTOGRAPHY ; CROSSING FIBERS ; DIFFUSION MRI ; RESOLUTION ; BRAIN ; CONNECTIVITY ; DISEASE ; VALIDATION ; INTEGRITY
WOS研究方向	Engineering ; Radiology, Nuclear Medicine & Medical Imaging
语种	英语
WOS记录号	WOS:000390513400005
资助机构	NIH/NINDS(5R01NS056307 ; China Scholarship Council ; 1R21NS082891)
内容类型	期刊论文
源URL	[http://ir.ia.ac.cn/handle/173211/12099]
专题	自动化研究所_脑网络组研究中心
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
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.