Linked Life Data

20144190

Source:http://linkedlifedata.com/resource/pubmed/id/20144190

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:dateCreated
2010-3-3
pubmed:abstractText
Using 3D generic models to statistically analyze trends in biological structure changes is an important tool in morphometrics research. Therefore, 3D generic models built for a range of populations are in high demand. However, due to the complexity of biological structures and the limited views of them that medical images can offer, it is still an exceptionally difficult task to quickly and accurately create 3D generic models (a model is a 3D graphical representation of a biological structure) based on medical image stacks (a stack is an ordered collection of 2D images). We show that the creation of a generic model that captures spatial information exploitable in statistical analyses is facilitated by coupling our generalized segmentation method to existing automatic image registration algorithms.
pubmed:commentsCorrections
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:issn
1471-2342
pubmed:author
pubmed:issnType
Electronic
pubmed:volume
10
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
5
pubmed:dateRevised
2010-9-28
pubmed:meshHeading
pubmed:year
2010
pubmed:articleTitle
Building generic anatomical models using virtual model cutting and iterative registration.
pubmed:affiliation
Sun Center of Excellence for Visual Genomics, Department of Biochemistry and Molecular Biology, Faculty of Medicine, University of Calgary, 3330 Hospital Drive NW, Calgary, T2N 4N1, Canada. mxiao@ucalgary.ca.
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't