Linked Life Data

16235661

Source:http://linkedlifedata.com/resource/pubmed/id/16235661

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
10
pubmed:dateCreated
2005-10-20
pubmed:abstractText
Body segment parameters are essential data in biomechanics. They are usually computed with population-specific predictive equations from literature. Recently, medical imaging and video-based methods were also reported for personalized computation. However, these methods present limitations: some of them provide only two-dimensional measurements or external measurements, others require a lot of tomographic images for a three-dimensional (3-D) reconstruction. Therefore, an original method is proposed to compute personalized body segment parameters from biplanar radiography. Simultaneous low-dose frontal and sagittal radiographs were obtained with EOS system. The upper leg segments of eight young males and eight young females were studied. The personalized parameters computed from the biplanar radiographic 3-D reconstructions were compared to literature. The biplanar radiographic method was consistent with predictive equations based on gamma-ray scan and dual energy X-ray absorptiometry.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Oct
pubmed:issn
0018-9294
pubmed:author
pubmed:issnType
Print
pubmed:volume
52
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
1756-63
pubmed:dateRevised
2009-11-11
pubmed:meshHeading
pubmed:year
2005
pubmed:articleTitle
Personalized body segment parameters from biplanar low-dose radiography.
pubmed:affiliation
Laboratoire de recherche en imagerie et orthopédie, Ecole de Technologie Supérieure, Montreal, Montreal, QC H3C 1K3, Canada.
pubmed:publicationType
Journal Article, Comparative Study, Research Support, Non-U.S. Gov't, Evaluation Studies, Validation Studies