A Novel Richardson-Lucy Model with Dictionary Basis and Spatial Regularization for Isolating Isotropic Signals

doi:10.1371/journal.pone.0168864

科研成果详情

题名	A Novel Richardson-Lucy Model with Dictionary Basis and Spatial Regularization for Isolating Isotropic Signals
作者	Xu, Tiantian 1; Feng, Yuanjing 1; Wu, Ye 1; Zeng, Qingrun 1; Zhang, Jun 1; He, Jianzhong 1; Zhuge, Qichuan2
发表日期	2017-01-12
发表期刊	PLOS ONE 影响因子和分区
语种	英语
原始文献类型	Article
其他关键词	CONSTRAINED SPHERICAL DECONVOLUTION ; DIFFUSION MRI DATA ; HUMAN BRAIN ; FIBER ORIENTATIONS ; WEIGHTED MRI ; RECONSTRUCTION ; TRACTOGRAPHY ; TENSOR ; ANISOTROPY ; ARCHITECTURE
摘要	Diffusion-weighted magnetic resonance imaging is a non-invasive imaging method that has been increasingly used in neuroscience imaging over the last decade. Partial volume effects (PVEs) exist in sampling signal for many physical and actual reasons, which lead to inaccurate fiber imaging. We overcome the influence of PVEs by separating isotropic signal from diffusion-weighted signal, which can provide more accurate estimation of fiber orientations. In this work, we use a novel response function (RF) and the correspondent fiber orientation distribution function (fODF) to construct different signal models, in which case the fODF is represented using dictionary basis function. We then put forward a new index P-iso, which is a part of fODF to quantify white and gray matter. The classic Richardson-Lucy (RL) model is usually used in the field of digital image processing to solve the problem of spherical deconvolution caused by highly ill-posed least-squares algorithm. In this case, we propose an innovative model integrating RL model with spatial regularization to settle the suggested double-models, which improve noise resistance and accuracy of imaging. Experimental results of simulated and real data show that the proposal method, which we call iRL, can robustly reconstruct a more accurate fODF and the quantitative index Piso performs better than fractional anisotropy and general fractional anisotropy.
资助项目	National Natural Science Foundation of ChinaNational Natural Science Foundation of China (NSFC) [61379020]; open foundation of Wenzhou Medical University [LKFJ014]
出版者	PUBLIC LIBRARY SCIENCE
出版地	SAN FRANCISCO
ISSN	1932-6203
卷号	12 期号:1 页码:e0168864.
DOI	10.1371/journal.pone.0168864
页数	21
WOS类目	Multidisciplinary Sciences
WOS研究方向	Science & Technology - Other Topics
WOS记录号	WOS:000391949500021
收录类别	SCIE ; PUBMED ; SCOPUS
URL	查看原文
PubMed ID	28081561
PMC记录号	PMC5233428
SCOPUSEID	2-s2.0-85009431374
通讯作者地址	[Feng, Yuanjing]Zhejiang Univ Technol, Inst Informat Proc & Automat, Hangzhou, Zhejiang, Peoples R China.
Scopus学科分类	Multidisciplinary
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	https://kms.wmu.edu.cn/handle/3ETUA0LF/18331
专题	第一临床医学院（信息与工程学院）、附属第一医院_老化与神经疾病重点实验室
通讯作者	Feng, Yuanjing
作者单位	1.Zhejiang Univ Technol, Inst Informat Proc & Automat, Hangzhou, Zhejiang, Peoples R China; 2.Wenzhou Med Univ, Zhejiang Prov Key Lab Aging & Neurol Disorder Res, Wenzhou, Zhejiang, Peoples R China
推荐引用方式 GB/T 7714	Xu, Tiantian,Feng, Yuanjing,Wu, Ye,et al. A Novel Richardson-Lucy Model with Dictionary Basis and Spatial Regularization for Isolating Isotropic Signals[J]. PLOS ONE,2017,12(1):e0168864..
APA	Xu, Tiantian., Feng, Yuanjing., Wu, Ye., Zeng, Qingrun., Zhang, Jun., ... & Zhuge, Qichuan. (2017). A Novel Richardson-Lucy Model with Dictionary Basis and Spatial Regularization for Isolating Isotropic Signals. PLOS ONE, 12(1), e0168864..
MLA	Xu, Tiantian,et al."A Novel Richardson-Lucy Model with Dictionary Basis and Spatial Regularization for Isolating Isotropic Signals".PLOS ONE 12.1(2017):e0168864..