Automatic Extraction of Femur Contours from Calibrated Fluoroscopic Images

Authors:
Xiao Dong;Miguel A. Gonzalez Ballester;Guoyan Zheng
Affiliations:
University of Bern, MEM Research Center, Bern, Switzerland;University of Bern, MEM Research Center, Bern, Switzerland;University of Bern, MEM Research Center, Bern, Switzerland
Venue:
WACV '07 Proceedings of the Eighth IEEE Workshop on Applications of Computer Vision
Year:
2007

Citing 0
Cited 2

Automatic reconstruction of a patient-specific surface model of a proximal femur from calibrated x-ray images via Bayesian filters

ICIC'07 Proceedings of the intelligent computing 3rd international conference on Advanced intelligent computing theories and applications
Unsupervised reconstruction of a patient-specific surface model of a proximal femur from calibrated fluoroscopic images

MICCAI'07 Proceedings of the 10th international conference on Medical image computing and computer-assisted intervention - Volume Part I

Quantified Score

Hi-index	0.00

Visualization

Abstract

Automatic identification and extraction of bone contours from x-ray images is an essential first step task for further medical image analysis. In this paper we propose a 3D statistical model based framework for the proximal femur contour extraction from calibrated x-ray images. The automatic initialization is solved by an Estimation of Bayesian Network Algorithm to fit a multiple component geometrical model to the x-ray data. The contour extraction is accomplished by a non-rigid 2D/3D registration between a 3D statistical model and the x-ray images, in which bone contours are extracted by a graphical model based Bayesian inference. Preliminary experiments on clinical data sets verified its validity.