A multimethod approach to the differentiation of enthesis bone microstructure based on soft tissue type

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dc.contributor.authorWhitebone, S Amber
dc.contributor.authorBari, A S M Hossain
dc.contributor.authorGavrilova, Marina L
dc.contributor.authorAnderson, Jason S
dc.date.accessioned2022-09-21T21:11:54Z
dc.date.available2022-09-21T21:11:54Z
dc.date.issued2021-06
dc.description.abstractWhereas there is a wealth of research studying the nature of various soft tissues that attach to bone, comparatively little research focuses on the bone's microscopic properties in the area where these tissues attach. Using scanning electron microscopy to generate a dataset of 1600 images of soft tissue attachment sites, an image classification program with novel convolutional neural network architecture can categorize images of attachment areas by soft tissue type based on observed patterns in microstructure morphology. Using stained histological thin section and liquid crystal cross-polarized microscopy, it is determined that soft tissue type can be quantitatively determined from the microstructure. The primary diagnostic characters are the orientation of collagen fibers and heterogeneity of collagen density throughout the attachment area thickness. These determinations are made across broad taxonomic sampling and multiple skeletal elements.en_US
dc.description.grantingagencyNatural Sciences and Engineering Research Council (NSERC)en_US
dc.identifier.citationWhitebone, S. A., Bari, A. S. M. H., Gavrilova, M. L., & Anderson, J. S. (2021). A multimethod approach to the differentiation of enthesis bone microstructure based on soft tissue type. Journal of Morphology, 282(9), 1362–1373. https://doi.org/10.1002/jmor.21391en_US
dc.identifier.doihttp://dx.doi.org/10.1002/jmor.21391en_US
dc.identifier.grantnumber2017-04821en_US
dc.identifier.issn1097-4687
dc.identifier.urihttp://hdl.handle.net/1880/115252
dc.identifier.urihttps://doi.org/10.11575/PRISM/46310
dc.publisherWileyen_US
dc.publisher.departmentBiological Sciencesen_US
dc.publisher.facultyScienceen_US
dc.publisher.facultyVeterinary Medicineen_US
dc.publisher.hasversionacceptedVersionen_US
dc.publisher.institutionUniversity of Calgaryen_US
dc.publisher.policyhttps://authorservices.wiley.com/author-resources/Journal-Authors/licensing/self-archiving.htmlen_US
dc.rightsUnless otherwise indicated, this material is protected by copyright and has been made available with authorization from the copyright owner. You may use this material in any way that is permitted by the Copyright Act or through licensing that has been assigned to the document. For uses that are not allowable under copyright legislation or licensing, you are required to seek permission.en_US
dc.subjectanatomyen_US
dc.subjectconvolutional neural networken_US
dc.subjectcross-polarized light microscopyen_US
dc.subjectEnthesisen_US
dc.subjectimage classificationen_US
dc.subjectscanning electron microscopyen_US
dc.subjectsoft tissue reconstructionen_US
dc.subjectvertebrate paleontologyen_US
dc.titleA multimethod approach to the differentiation of enthesis bone microstructure based on soft tissue typeen_US
dc.typejournal articleen_US
ucalgary.item.requestcopyfalseen_US
ucalgary.scholar.levelFaculty, graduateen_US
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