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Automatic segmentation of the glenohumeral cartilages from magnetic resonance images
Neubert, A.1,2; Yang, Z.1,3; Engstrom, C.4; Xia, Y.1; Strudwick, M. W.1; Chandra, S. S.1; Fripp, J.2; Crozier, S.1
Source PublicationMEDICAL PHYSICS
2016-10-01
Volume43Issue:10
SubtypeArticle
AbstractPurpose: Magnetic resonance (MR) imaging plays a key role in investigating early degenerative disorders and traumatic injuries of the glenohumeral cartilages. Subtle morphometric and biochemical changes of potential relevance to clinical diagnosis, treatment planning, and evaluation can be assessed from measurements derived from in vivo MR segmentation of the cartilages. However, segmentation of the glenohumeral cartilages, using approaches spanning manual to automated methods, is technically challenging, due to their thin, curved structure and overlapping intensities of surrounding tissues. Automatic segmentation of the glenohumeral cartilages from MR imaging is not at the same level compared to the weight-bearing knee and hip joint cartilages despite the potential applications with respect to clinical investigation of shoulder disorders. In this work, the authors present a fully automated segmentation method for the glenohumeral cartilages using MR images of healthy shoulders.
KeywordImage Segmentation Glenohumeral Cartilage Magnetic Resonance Imaging Statistical Shape Models Morphological Analysis
WOS HeadingsScience & Technology ; Life Sciences & Biomedicine
DOI10.1118/1.4961011
WOS Keyword3D MR-IMAGES ; ARTICULAR-CARTILAGE ; THICKNESS MEASUREMENTS ; BONE SEGMENTATION ; SHAPE MODELS ; SHOULDER MRI ; KNEE-JOINT ; HIP-JOINT ; EXTRACTION ; OSTEOARTHRITIS
Indexed BySCI
Language英语
Funding OrganizationAustralian Research Council's Linkage Projects(LP100200422) ; National Health and Medical Research Council's Development Grant(APP1091996)
WOS Research AreaRadiology, Nuclear Medicine & Medical Imaging
WOS SubjectRadiology, Nuclear Medicine & Medical Imaging
WOS IDWOS:000385577900012
Citation statistics
Cited Times:2[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/13323
Collection脑网络组研究中心
Affiliation1.Univ Queensland, Sch Informat Technol & Elect Engn, Brisbane, Qld 4072, Australia
2.CSIRO Hlth & Biosecur, Australian E Hlth Res Ctr, Brisbane, Qld 4029, Australia
3.Chinese Acad Sci, Brainnetome Ctr, Inst Automat, Beijing 100190, Peoples R China
4.Univ Queensland, Sch Human Movement Studies, Brisbane, Qld 4072, Australia
Recommended Citation
GB/T 7714
Neubert, A.,Yang, Z.,Engstrom, C.,et al. Automatic segmentation of the glenohumeral cartilages from magnetic resonance images[J]. MEDICAL PHYSICS,2016,43(10).
APA Neubert, A..,Yang, Z..,Engstrom, C..,Xia, Y..,Strudwick, M. W..,...&Crozier, S..(2016).Automatic segmentation of the glenohumeral cartilages from magnetic resonance images.MEDICAL PHYSICS,43(10).
MLA Neubert, A.,et al."Automatic segmentation of the glenohumeral cartilages from magnetic resonance images".MEDICAL PHYSICS 43.10(2016).
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