| Literature DB >> 20703627 |
Abdurrahim Akgundogdu1, Rachid Jennane, Gabriel Aufort, Claude Laurent Benhamou, Osman Nuri Ucan.
Abstract
In order to prevent bone fractures due to disease and ageing of the population, and to detect problems while still in their early stages, 3D bone micro architecture needs to be investigated and characterized. Here, we have developed various image processing and simulation techniques to investigate bone micro architecture and its mechanical stiffness. We have evaluated morphological, topological and mechanical bone features using artificial intelligence methods. A clinical study is carried out on two populations of arthritic and osteoporotic bone samples. The performances of Adaptive Neuro Fuzzy Inference System (ANFIS), Support Vector Machines (SVM) and Genetic Algorithm (GA) in classifying the different samples have been compared. Results show that the best separation success (100 %) is achieved with Genetic Algorithm.Entities:
Mesh:
Year: 2009 PMID: 20703627 DOI: 10.1007/s10916-009-9296-3
Source DB: PubMed Journal: J Med Syst ISSN: 0148-5598 Impact factor: 4.460