edoc

Prediction of biomechanical parameters of the proximal femur using statistical appearance models and support vector regression

Fritscher, Karl and Schuler, Benedikt and Link, Thomas and Eckstein, Felix and Suhm, Norbert and Hänni, Markus and Hengg, Clemens and Schubert, Rainer. (2008) Prediction of biomechanical parameters of the proximal femur using statistical appearance models and support vector regression. Medical image computing and computer-assisted intervention, Vol. 11, H. 1. pp. 568-575.

Full text not available from this repository.

Official URL: http://edoc.unibas.ch/dok/A6004605

Downloads: Statistics Overview

Abstract

Fractures of the proximal femur are one of the principal causes of mortality among elderly persons. Traditional methods for the determination of femoral fracture risk use methods for measuring bone mineral density. However, BMD alone is not sufficient to predict bone failure load for an individual patient and additional parameters have to be determined for this purpose. In this work an approach that uses statistical models of appearance to identify relevant regions and parameters for the prediction of biomechanical properties of the proximal femur will be presented. By using Support Vector Regression the proposed model based approach is capable of predicting two different biomechanical parameters accurately and fully automatically in two different testing scenarios.
Faculties and Departments:03 Faculty of Medicine > Bereich Operative Fächer (Klinik) > Innere Organe > Allgemein- und Viszeralchirurgie (Oertli)
03 Faculty of Medicine > Departement Klinische Forschung > Bereich Operative Fächer (Klinik) > Innere Organe > Allgemein- und Viszeralchirurgie (Oertli)
UniBasel Contributors:Suhm, Norbert
Item Type:Article, refereed
Article Subtype:Research Article
Bibsysno:Link to catalogue
Publisher:Springer
Note:Publication type according to Uni Basel Research Database: Journal article
Related URLs:
Identification Number:
Last Modified:08 Nov 2013 08:29
Deposited On:08 Nov 2013 08:29

Repository Staff Only: item control page