Linked Life Data

10828326

Source:http://linkedlifedata.com/resource/pubmed/id/10828326

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
8
pubmed:dateCreated
2000-8-16
pubmed:abstractText
A quantitative biomechanical model describes the tissue transformation during healing of a transverse osteotomy of a sheep metatarsal. The model predicts bridging of the bone ends through cartilage, followed by the growth of a callus cuff, and finally, the resorption of callus after ossification of the interfragmentary gap. We suggest bone density or the modulus of elasticity do not sufficiently characterize healing tissue for predictive purposes. In addition to the stimulus reflected by strain energy density we introduce a new osteogenic factor based upon stress gradients and which predicts areas of a high osteogenic capacity. Our model distinguishes three basic types of tissue, namely bone, cartilage and fibrous tissue. A fuzzy controller is proposed to model the tissue reaction. A set of fuzzy rules derived from medical knowledge has been implemented to describe tissue transformation such as intramembraneous or chondral ossification, atrophy or destruction. Fuzzy logic is able to model tissue transformation processes within the numerical simulation of remodeling processes. This approach improves the simulation tools and affords the potential to optimize planning of animal experiments and conduct parametric studies.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Aug
pubmed:issn
0021-9290
pubmed:author
pubmed:issnType
Print
pubmed:volume
33
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
961-8
pubmed:dateRevised
2009-11-11
pubmed:meshHeading
pubmed:year
2000
pubmed:articleTitle
A fuzzy logic model of fracture healing.
pubmed:affiliation
Department of Measurement and Control, University of Bremen, Germany.
pubmed:publicationType
Journal Article