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Automated cerebellar lobule segmentation with application to cerebellar structural analysis in cerebellar disease

文献类型：期刊论文

作者Yang, Zhen1; Ye, Chuyang2,3; Bogovic, John A.4; Carass, Aaron1,5; Jedynak, Bruno M.6; Ying, Sarah H.7; Prince, Jerry L.1,5,6,7; Zhen Yang
刊名NEUROIMAGE
出版日期2016-02-15
卷号127期号:1页码:435-444
关键词Cerebellum Cerebellar Lobule Segmentation Graph Cuts Magnetic Resonance Imaging Multi-atlas Labeling Random Forest Classifier Spinocerebellar Ataxia
DOI10.1016/j.neuroimage.2015.09.032
文献子类Article
英文摘要The cerebellum plays an important role in both motor control and cognitive function. Cerebellar function is topographically organized and diseases that affect specific parts of the cerebellum are associated with specific patterns of symptoms. Accordingly, delineation and quantification of cerebellar sub-regions from magnetic resonance images are important in the study of cerebellar atrophy and associated functional losses. This paper describes an automated cerebellar lobule segmentation method based on a graph cut segmentation framework. Results from multi-atlas labeling and tissue classification contribute to the region terms in the graph cut energy function and boundary classification contributes to the boundary term in the energy function. A cerebellar parcellation is achieved by minimizing the energy function using the a-expansion technique. The proposed method was evaluated using a leave-one-out cross-validation on 15 subjects including both healthy controls and patients with cerebellar diseases. Based on reported Dice coefficients, the proposed method outperforms two state-of-the-art methods. The proposed method was then applied to 77 subjects to study the region-specific cerebellar structural differences in three spinocerebellar ataxia (SCA) genetic subtypes. Quantitative analysis of the lobule volumes shows distinct patterns of volume changes associated with different SCA subtypes consistent with known patterns of atrophy in these genetic subtypes. (C) 2015 Elsevier Inc. All rights reserved.
WOS关键词IMAGE SEGMENTATION ; HUNTINGTONS-DISEASE ; STATISTICAL FUSION ; LABEL-FUSION ; GRAPH CUTS ; BRAIN ; ATLAS ; ATROPHY ; PERFORMANCE ; DEGENERATION
WOS研究方向Neurosciences & Neurology ; Radiology, Nuclear Medicine & Medical Imaging
语种英语
WOS记录号WOS:000369952900037
资助机构NIH/NINDS(5R01NS056307-08)
源URL[http://ir.ia.ac.cn/handle/173211/11341]  
专题自动化研究所_脑网络组研究中心
通讯作者Zhen Yang
作者单位1.Johns Hopkins Univ, Dept Elect & Comp Engn, 105 Barton Hall,3400 N Charles St, Baltimore, MD 21218 USA
2.Chinese Acad Sci, Brainnetome Ctr, Beijing 100190, Peoples R China
3.Chinese Acad Sci, Natl Lab Pattern Recognit, Inst Automat, Beijing 100190, Peoples R China
4.Howard Hughes Med Inst, Janelia Res Campus, Ashburn, VA 20147 USA
5.Johns Hopkins Univ, Dept Comp Sci, Baltimore, MD 21218 USA
6.Johns Hopkins Univ, Dept Appl Math & Stat, Baltimore, MD 21218 USA
7.Johns Hopkins Sch Med, Dept Radiol, Baltimore, MD 21287 USA
推荐引用方式
GB/T 7714		 Yang, Zhen,Ye, Chuyang,Bogovic, John A.,et al. Automated cerebellar lobule segmentation with application to cerebellar structural analysis in cerebellar disease[J]. NEUROIMAGE,2016,127(1):435-444.
APA Yang, Zhen.,Ye, Chuyang.,Bogovic, John A..,Carass, Aaron.,Jedynak, Bruno M..,...&Zhen Yang.(2016).Automated cerebellar lobule segmentation with application to cerebellar structural analysis in cerebellar disease.NEUROIMAGE,127(1),435-444.
MLA Yang, Zhen,et al."Automated cerebellar lobule segmentation with application to cerebellar structural analysis in cerebellar disease".NEUROIMAGE 127.1(2016):435-444.

入库方式： OAI收割

来源：自动化研究所

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