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A Bayesian approach to distinguishing interdigitated tongue muscles from limited diffusion magnetic resonance imaging
Ye, Chuyang1,2; Murano, Erni3; Stone, Maureen4; Prince, Jerry L.2; Chuyang Ye
Source PublicationCOMPUTERIZED MEDICAL IMAGING AND GRAPHICS
2015-10-01
Volume45Issue:1Pages:63-74
SubtypeArticle
AbstractThe tongue is a critical organ for a variety of functions, including swallowing, respiration, and speech. It contains intrinsic and extrinsic muscles that play an important role in changing its shape and position. Diffusion tensor imaging (DTI) has been used to reconstruct tongue muscle fiber tracts. However, previous studies have been unable to reconstruct the crossing fibers that occur where the tongue muscles interdigitate, which is a large percentage of the tongue volume. To resolve crossing fibers, multi-tensor models on DTI and more advanced imaging modalities, such as high angular resolution diffusion imaging (HARDI) and diffusion spectrum imaging (DSI), have been proposed. However, because of the involuntary nature of swallowing, there is insufficient time to acquire a sufficient number of diffusion gradient directions to resolve crossing fibers while the in vivo tongue is in a fixed position. In this work, we address the challenge of distinguishing interdigitated tongue muscles from limited diffusion magnetic resonance imaging by using a multi-tensor model with a fixed tensor basis and incorporating prior directional knowledge. The prior directional knowledge provides information on likely fiber directions at each voxel, and is computed with anatomical knowledge of tongue muscles. The fiber directions are estimated within a maximum a posteriori (MAP) framework, and the resulting objective function is solved using a noise-aware weighted l(1)-norm minimization algorithm. Experiments were performed on a digital crossing phantom and in vivo tongue diffusion data including three control subjects and four patients with glossectomies. On the digital phantom, effects of parameters, noise, and prior direction accuracy were studied, and parameter settings for real data were determined. The results on the in vivo data demonstrate that the proposed method is able to resolve interdigitated tongue muscles with limited gradient directions. The distributions of the computed fiber directions in both the controls and the patients were also compared, suggesting a potential clinical use for this imaging and image analysis methodology. (C) 2015 Elsevier Ltd. All rights reserved.
KeywordDiffusion Magnetic Resonance Imaging Limited Gradient Directions Sparse Reconstruction Prior Directional Knowledge Interdigitated Tongue Muscles
WOS HeadingsScience & Technology ; Technology ; Life Sciences & Biomedicine
DOI10.1016/j.compmedimag.2015.07.005
WOS KeywordTENSOR MRI ; IN-VIVO ; TRACTOGRAPHY ; ARCHITECTURE ; BRAIN ; MODEL ; MYOARCHITECTURE ; SEGMENTATION ; RESOLUTION ; TRACTS
Indexed BySCI
Language英语
Funding OrganizationNIH/NINDS(1R21NS082891 ; NIH/NCI(5R01CA133015) ; China Scholarship Council ; 5R01NS056307)
WOS Research AreaEngineering ; Radiology, Nuclear Medicine & Medical Imaging
WOS SubjectEngineering, Biomedical ; Radiology, Nuclear Medicine & Medical Imaging
WOS IDWOS:000364891200007
Citation statistics
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/10512
Collection脑网络组研究中心
Corresponding AuthorChuyang Ye
Affiliation1.Chinese Acad Sci, Inst Automat, Brainnetome Ctr, Beijing, Peoples R China
2.Johns Hopkins Univ, Dept Elect & Comp Engn, Baltimore, MD 21218 USA
3.Johns Hopkins Univ, Sch Med, Dept Radiol & Radiol Sci, Baltimore, MD USA
4.Univ Maryland, Sch Dent, Dept Neural & Pain Sci, Baltimore, MD 21201 USA
Recommended Citation
GB/T 7714
Ye, Chuyang,Murano, Erni,Stone, Maureen,et al. A Bayesian approach to distinguishing interdigitated tongue muscles from limited diffusion magnetic resonance imaging[J]. COMPUTERIZED MEDICAL IMAGING AND GRAPHICS,2015,45(1):63-74.
APA Ye, Chuyang,Murano, Erni,Stone, Maureen,Prince, Jerry L.,&Chuyang Ye.(2015).A Bayesian approach to distinguishing interdigitated tongue muscles from limited diffusion magnetic resonance imaging.COMPUTERIZED MEDICAL IMAGING AND GRAPHICS,45(1),63-74.
MLA Ye, Chuyang,et al."A Bayesian approach to distinguishing interdigitated tongue muscles from limited diffusion magnetic resonance imaging".COMPUTERIZED MEDICAL IMAGING AND GRAPHICS 45.1(2015):63-74.
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