Morphometry Based on Effective and Accurate Correspondences of Localized Patterns (MEACOLP)

CORC > 自动化研究所 > 中国科学院自动化研究所 > 中国科学院分子影像重点实验室

	Morphometry Based on Effective and Accurate Correspondences of Localized Patterns (MEACOLP)
	Wang, Hu 1; Ren, Yanshuang 2; Bai, Lijun 1; Zhang, Wensheng1 ; Tian, Jie1,3
刊名	PLOS ONE
	2012-04-23
卷号	7 期号:4 页码:-
英文摘要	Local features in volumetric images have been used to identify correspondences of localized anatomical structures for brain morphometry. However, the correspondences are often sparse thus ineffective in reflecting the underlying structures, making it unreliable to evaluate specific morphological differences. This paper presents a morphometry method (MEACOLP) based on correspondences with improved effectiveness and accuracy. A novel two-level scale-invariant feature transform is used to enhance the detection repeatability of local features and to recall the correspondences that might be missed in previous studies. Template patterns whose correspondences could be commonly identified in each group are constructed to serve as the basis for morphometric analysis. A matching algorithm is developed to reduce the identification errors by comparing neighboring local features and rejecting unreliable matches. The two-sample t-test is finally adopted to analyze specific properties of the template patterns. Experiments are performed on the public OASIS database to clinically analyze brain images of Alzheimer's disease (AD) and normal controls (NC). MEACOLP automatically identifies known morphological differences between AD and NC brains, and characterizes the differences well as the scaling and translation of underlying structures. Most of the significant differences are identified in only a single hemisphere, indicating that AD-related structures are characterized by strong anatomical asymmetry. In addition, classification trials to differentiate AD subjects from NC confirm that the morphological differences are reliably related to the groups of interest.
WOS标题词	Science & Technology
类目[WOS]	Multidisciplinary Sciences
研究领域[WOS]	Science & Technology - Other Topics
关键词[WOS]	VOXEL-BASED MORPHOMETRY ; MILD COGNITIVE IMPAIRMENT ; ALZHEIMERS-DISEASE ; MRI ; ATROPHY ; BRAIN ; CLASSIFICATION ; VENTRICLES ; DIAGNOSIS
收录类别	SCI
语种	英语
WOS记录号	WOS:000305341000066
内容类型	期刊论文
源URL	[http://ir.ia.ac.cn/handle/173211/4020]
专题	自动化研究所_中国科学院分子影像重点实验室
作者单位	1.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing, Peoples R China 2.Chinese Acad Tradit Med, Guanganmen Hosp, Dept Radiol, Beijing, Peoples R China 3.Xidian Univ, Sch Elect Engn, Life Sci Res Ctr, Xian, Peoples R China
推荐引用方式 GB/T 7714	Wang, Hu,Ren, Yanshuang,Bai, Lijun,et al. Morphometry Based on Effective and Accurate Correspondences of Localized Patterns (MEACOLP)[J]. PLOS ONE,2012,7(4):-.
APA	Wang, Hu,Ren, Yanshuang,Bai, Lijun,Zhang, Wensheng,&Tian, Jie.(2012).Morphometry Based on Effective and Accurate Correspondences of Localized Patterns (MEACOLP).PLOS ONE,7(4),-.
MLA	Wang, Hu,et al."Morphometry Based on Effective and Accurate Correspondences of Localized Patterns (MEACOLP)".PLOS ONE 7.4(2012):-.