An integrated approach for reconstructing surface models of the proximal femur from sparse input data for surgical navigation

Zheng, Guoyan; Gonzalez Ballester, Miguel Angel (2007). An integrated approach for reconstructing surface models of the proximal femur from sparse input data for surgical navigation. In: Duffy, Vincent D (ed.) Digital Human Modeling: Proceedings of First International Conference, ICDHM 2007. Lecture Notes in Computer Science: Vol. 4561 (pp. 767-775). Beijing, China: Springer 10.1007/978-3-540-73321-8_88

Full text not available from this repository. (Request a copy)

A patient-specific surface model of the proximal femur plays an important role in planning and supporting various computer-assisted surgical procedures including total hip replacement, hip resurfacing, and osteotomy of the proximal femur. The common approach to derive 3D models of the proximal femur is to use imaging techniques such as computed tomography (CT) or magnetic resonance imaging (MRI). However, the high logistic effort, the extra radiation (CT-imaging), and the large quantity of data to be acquired and processed make them less functional. In this paper, we present an integrated approach using a multi-level point distribution model (ML-PDM) to reconstruct a patient-specific model of the proximal femur from intra-operatively available sparse data. Results of experiments performed on dry cadaveric bones using dozens of 3D points are presented, as well as experiments using a limited number of 2D X-ray images, which demonstrate promising accuracy of the present approach.

Item Type:

Conference or Workshop Item (Paper)

Division/Institute:

04 Faculty of Medicine > Pre-clinic Human Medicine > Institute for Surgical Technology & Biomechanics ISTB

UniBE Contributor:

Zheng, Guoyan and Gonzalez Ballester, Miguel Angel

Subjects:

500 Science > 570 Life sciences; biology
600 Technology > 610 Medicine & health

ISSN:

0302-9743

ISBN:

978-3-540-73321-8

Series:

Lecture Notes in Computer Science

Publisher:

Springer

Language:

English

Submitter:

Factscience Import

Date Deposited:

04 Oct 2013 14:57

Last Modified:

02 May 2014 14:28

Publisher DOI:

10.1007/978-3-540-73321-8_88

URI:

https://boris.unibe.ch/id/eprint/24199 (FactScience: 47431)

Actions (login required)

Edit item Edit item
Provide Feedback