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Metric Learning for Multi-atlas based Segmentation of Hippocampus
Zhu, Hancan1; Cheng, Hewei2; Yang, Xuesong3; Fan, Yong4; Alzheimer's Dis Neuroimaging
Source PublicationNEUROINFORMATICS
2017
Volume15Issue:1Pages:41-50
SubtypeArticle
AbstractAutomatic and reliable segmentation of hippocampus from MR brain images is of great importance in studies of neurological diseases, such as epilepsy and Alzheimer's disease. In this paper, we proposed a novel metric learning method to fuse segmentation labels in multi-atlas based image segmentation. Different from current label fusion methods that typically adopt a predefined distance metric model to compute a similarity measure between image patches of atlas images and the image to be segmented, we learn a distance metric model from the atlases to keep image patches of the same structure close to each other while those of different structures are separated. The learned distance metric model is then used to compute the similarity measure between image patches in the label fusion. The proposed method has been validated for segmenting hippocampus based on the EADC-ADNI dataset with manually labelled hippocampus of 100 subjects. The experiment results demonstrated that our method achieved statistically significant improvement in segmentation accuracy, compared with state-of-the-art multi-atlas image segmentation methods.
KeywordMulti-atlas Image Segmentation Hippocampus Segmentation Metric Learning Label Fusion
WOS HeadingsScience & Technology ; Technology ; Life Sciences & Biomedicine
DOI10.1007/s12021-016-9312-y
WOS KeywordIMAGE SEGMENTATION ; LABEL FUSION ; ALZHEIMERS-DISEASE ; BRAIN ; SELECTION ; PATCH ; CLASSIFICATION ; REGISTRATION ; PERFORMANCE ; VALIDATION
Indexed BySCI
Language英语
Funding OrganizationNational Key Basic Research and Development Program(2015CB856404) ; National Natural Science Foundation of China(81271514 ; NIH(EB022573 ; 61473296 ; CA189523 ; 61602307) ; AG014971)
WOS Research AreaComputer Science ; Neurosciences & Neurology
WOS SubjectComputer Science, Interdisciplinary Applications ; Neurosciences
WOS IDWOS:000394260000005
Citation statistics
Cited Times:9[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/14387
Collection脑网络组研究中心
Affiliation1.Shaoxing Univ, Sch Math Phys & Informat, Shaoxing 312000, Peoples R China
2.Chongqing Univ Posts & Telecommun, Sch Bioinformat, Dept Biomed Engn, Chongqing 400065, Peoples R China
3.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China
4.Univ Penn, Dept Radiol, Perelman Sch Med, Philadelphia, PA 19104 USA
Recommended Citation
GB/T 7714
Zhu, Hancan,Cheng, Hewei,Yang, Xuesong,et al. Metric Learning for Multi-atlas based Segmentation of Hippocampus[J]. NEUROINFORMATICS,2017,15(1):41-50.
APA Zhu, Hancan,Cheng, Hewei,Yang, Xuesong,Fan, Yong,&Alzheimer's Dis Neuroimaging.(2017).Metric Learning for Multi-atlas based Segmentation of Hippocampus.NEUROINFORMATICS,15(1),41-50.
MLA Zhu, Hancan,et al."Metric Learning for Multi-atlas based Segmentation of Hippocampus".NEUROINFORMATICS 15.1(2017):41-50.
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