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Fully automatic segmentation of femurs with medullary canal definition in high and in low resolution CT scans

2016-12Journal article Restricted access
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dc.contributor.authorAlmeida, Diogo F.
dc.contributor.authorRuben, Rui
dc.contributor.authorFolgado, João
dc.contributor.authorFernandes, Paulo R.
dc.contributor.authorAudenaert, Emmanuel
dc.contributor.authorVerhegghe, Benedict
dc.contributor.authorDe Beule, Matthieu
dc.date.accessioned2025-05-23T16:27:12Z
dc.date.available2025-05-23T16:27:12Z
dc.date.issued2016-12
dc.description.abstractFemur segmentation can be an important tool in orthopedic surgical planning. However, in order to over- come the need of an experienced user with extensive knowledge on the techniques, segmentation should be fully automatic. In this paper a new fully automatic femur segmentation method for CT images is pre- sented. This method is also able to define automatically the medullary canal and performs well even in low resolution CT scans. Fully automatic femoral segmentation was performed adapting a template mesh of the femoral vol- ume to medical images. In order to achieve this, an adaptation of the active shape model (ASM) tech- nique based on the statistical shape model (SSM) and local appearance model (LAM) of the femur with a novel initialization method was used, to drive the template mesh deformation in order to fit the in-image femoral shape in a time effective approach. With the proposed method a 98% convergence rate was achieved. For high resolution CT images group the average error is less than 1 mm. For the low resolution image group the results are also accurate and the average error is less than 1.5 mm. The proposed segmentation pipeline is accurate, robust and completely user free. The method is ro- bust to patient orientation, image artifacts and poorly defined edges. The results excelled even in CT images with a significant slice thickness, i.e., above 5 mm. Medullary canal segmentation increases the geometric information that can be used in orthopedic surgical planning or in finite element analysis.por
dc.description.sponsorshipThis work was supported by FEDER through the operational program Competitiveness Factors –COMPETE, the Portuguese Foundation for Science and Technology (FCT), project PTDC/SAU- BEB/103408/2008, through scholarship SFRH/BD/71822/2010 , through IDMEC, under LAETA, project UID/EMS/50022/2013 and the University of Ghent, under the Special Research Fund (BOF) 01SF2613 .
dc.identifier.doi10.1016/j.medengphy.2016.09.019
dc.identifier.issn1350-4533
dc.identifier.urihttp://hdl.handle.net/10400.8/12973
dc.language.isoeng
dc.peerreviewedyes
dc.publisherElsevier BV
dc.relationPTDC/SAU- BEB/103408/2008
dc.relation.hasversionhttps://www.sciencedirect.com/science/article/abs/pii/S1350453316302193
dc.relation.ispartofMedical Engineering & Physics
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subject3D femur segmentation
dc.subjectCT image
dc.subjectActive shape model (ASM)
dc.subjectStatistical shape model (SSM)
dc.subjectTotal hip arthroplasty
dc.titleFully automatic segmentation of femurs with medullary canal definition in high and in low resolution CT scans
dc.typejournal article
dspace.entity.typePublication
oaire.citation.endPage1480
oaire.citation.issue12
oaire.citation.startPage1474
oaire.citation.titleMedical Engineering & Physics
oaire.citation.volume38
oaire.versionhttp://purl.org/coar/version/c_970fb48d4fbd8a85
person.familyNameRuben
person.givenNameRui
person.identifier46426
person.identifier.ciencia-id0A14-A279-7C05
person.identifier.orcid0000-0002-5407-0579
person.identifier.ridM-1119-2014
person.identifier.scopus-author-id7103127401
relation.isAuthorOfPublicatione69b86a2-a7dc-433d-94cb-0f3196fdc670
relation.isAuthorOfPublication.latestForDiscoverye69b86a2-a7dc-433d-94cb-0f3196fdc670

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