Repository logo
 
Publication

Separating positional noise from neutral alignment in multicomponent statistical shape models

2020-01Journal article Open access
Simple item page
dc.contributor.authorAudenaert, E. A.
dc.contributor.authorVan den Eyndeb, J.
dc.contributor.authorAlmeida, D. F. de
dc.contributor.authorSteenackers, G.
dc.contributor.authorVandermeulen, D.
dc.contributor.authorClaes, P.
dc.date.accessioned2023-04-18T15:52:46Z
dc.date.available2023-04-18T15:52:46Z
dc.date.issued2020-01
dc.description.abstractGiven sufficient training samples, statistical shape models can provide detailed population representations for use in anthropological and computational genetic studies, injury biomechanics, musculoskeletal disease models or implant design optimization. While the technique has become extremely popular for the description of isolated anatomical structures, it suffers from positional interference when applied to coupled or articulated input data. In the present manuscript we describe and validate a novel approach to extract positional noise from such coupled data. The technique was first validated and then implemented in a multicomponent model of the lower limb. The impact of noise on the model itself as well as on the description of sexual dimorphism was evaluated. The novelty of our methodology lies in the fact that no rigid transformations are calculated or imposed on the data by means of idealized joint definitions and by extension the models obtained from them.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationAudenaert, E. A., Van den Eynde, J., de Almeida, D. F., Steenackers, G., Vandermeulen, D., & Claes, P. (2020). Separating positional noise from neutral alignment in multicomponent statistical shape models. Bone Reports, 12. https://doi.org/10.1016/j.bonr.2020.100243pt_PT
dc.identifier.doi10.1016/j.bonr.2020.100243pt_PT
dc.identifier.issn2352-1872
dc.identifier.urihttp://hdl.handle.net/10400.8/8411
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherElsevierpt_PT
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/pt_PT
dc.subjectImage analysispt_PT
dc.subjectSex dimorphismpt_PT
dc.subjectGeometric morphometricspt_PT
dc.subjectMultivariate regressionpt_PT
dc.subjectAnatomypt_PT
dc.titleSeparating positional noise from neutral alignment in multicomponent statistical shape modelspt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.citation.titleBone Reportspt_PT
oaire.citation.volume12pt_PT
rcaap.rightsopenAccesspt_PT
rcaap.typearticlept_PT

Files

Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
Audenaert et al_2020_Separating positional noise from neutral aligment in multicomponent statistical sgape models.pdf
Size:
2.09 MB
Format:
Adobe Portable Document Format
Description:
Download
License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
1.32 KB
Format:
Item-specific license agreed upon to submission
Description:
Download

Collections

CDRsp - Artigos em revistas internacionais