Atlas-based segmentation of neck muscles from MRI for the characterisation of Whiplash Associated Disorder

dc.contributor.authorAl Suman, Abdulla
dc.contributor.authorAktar, Mst Nargis
dc.contributor.authorAsikuzzaman, Md
dc.contributor.authorWebb, Alexandra
dc.contributor.authorPerriman, Diana
dc.contributor.authorPickering, Mark
dc.contributor.editorJiang X.Falco C.M.
dc.coverage.spatialChengu, China
dc.date.accessioned2019-08-12T04:36:30Z
dc.date.available2019-08-12T04:36:30Z
dc.date.created20 May 2016 through 23 May 2016
dc.date.issued2016
dc.date.updated2019-11-25T07:21:45Z
dc.description.abstractWhiplash-associated disorder (WAD) is a commonly occurring injury that often results from neck trauma suffered in car accidents. However the cause of the condition is still unknown and there is no definitive clinical test for the presence of the condition. Researchers have begun to analyze the size of neck muscles and the presence of fatty infiltrates to help understand WAD. However this analysis requires a high precision delineation of neck muscles which is very challenging due to a lack of distinctive features in neck magnetic resonance imaging (MRI). This paper presents a novel atlas-based neck muscle segmentation method which employs discrete cosine-based elastic registration with affine initialization. Our algorithm shows promising results based on clinical data with an average Dice similarity coefficient (DSC) of 0.84±0.0004.
dc.format.mimetypeapplication/pdfen_AU
dc.identifier.isbn9780000000000
dc.identifier.urihttp://hdl.handle.net/1885/164994
dc.language.isoen_AUen_AU
dc.provenanceCopyright 2016 Society of Photo-Optical Instrumentation Engineers. One print or electronic copy may be made for personal use only. Systematic reproduction and distribution, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper are prohibited. Citation of the paper: Al Suman, Abdulla, et al. "Atlas-based segmentation of neck muscles from mri for the characterisation of whiplash associated disorder." Eighth International Conference on Digital Image Processing (ICDIP 2016). Vol. 10033, Article no. 100334L. International Society for Optics and Photonics, 2016.en_AU
dc.publisherSPIE - The International Society for Optical Engineering
dc.relation.ispartofseries8th International Conference on Digital Image Processing, ICDIP 2016
dc.rights© 2016 SPIE
dc.sourceProceedings of SPIE - The International Society for Optical Engineering
dc.titleAtlas-based segmentation of neck muscles from MRI for the characterisation of Whiplash Associated Disorder
dc.typeConference paper
dcterms.accessRightsOpen Accessen_AU
local.bibliographicCitation.lastpage100334L-5en_AU
local.bibliographicCitation.startpage100334L-1en_AU
local.contributor.affiliationAl Suman, Abdulla, University of New South Walesen_AU
local.contributor.affiliationAktar, Mst Nargis, UNSWen_AU
local.contributor.affiliationAsikuzzaman, Md, University of New South Walesen_AU
local.contributor.affiliationWebb, Alexandra, College of Health and Medicine, ANUen_AU
local.contributor.affiliationPerriman, Diana, College of Health and Medicine, ANUen_AU
local.contributor.affiliationPickering, Mark, University of New South Wales, ADFAen_AU
local.contributor.authoruidWebb, Alexandra, u5101252en_AU
local.contributor.authoruidPerriman, Diana, u4370058en_AU
local.description.notesImported from ARIESen_AU
local.description.refereedYes
local.identifier.absfor110320 - Radiology and Organ Imagingen_AU
local.identifier.absseo920116 - Skeletal System and Disorders (incl. Arthritis)en_AU
local.identifier.ariespublicationa383154xPUB4911en_AU
local.identifier.citationvolume10033en_AU
local.identifier.doi10.1117/12.2243754en_AU
local.identifier.scopusID2-s2.0-85000786727
local.identifier.thomsonID000391694700163
local.type.statusPublished Versionen_AU

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