3D volumetric intensity reconsturction from 2D x-ray images using partial least squares regression

Zheng, Guoyan (2013). 3D volumetric intensity reconsturction from 2D x-ray images using partial least squares regression. In: 10th International Symposium on Biomedical Imaging: From Nano to Macro (pp. 1268-1271). IEEE 10.1109/ISBI.2013.6556762

Full text not available from this repository.

Reconstruction of shape and intensity from 2D x-ray images has drawn more and more attentions. Previously introduced work suffers from the long computing time due to its iterative optimization characteristics and the requirement of generating digitally reconstructed radiographs within each iteration. In this paper, we propose a novel method which uses a patient-specific 3D surface model reconstructed from 2D x-ray images as a surrogate to get a patient-specific volumetric intensity reconstruction via partial least squares regression. No DRR generation is needed. The method was validated on 20 cadaveric proximal femurs by performing a leave-one-out study. Qualitative and quantitative results demonstrated the efficacy of the present method. Compared to the existing work, the present method has the advantage of much shorter computing time and can be applied to both DXA images as well as conventional x-ray images, which may hold the potentials to be applied to clinical routine task such as total hip arthroplasty (THA).

Item Type:	Conference or Workshop Item (Paper)
Division/Institute:	04 Faculty of Medicine > Pre-clinic Human Medicine > Institute for Surgical Technology & Biomechanics ISTB [discontinued]
UniBE Contributor:	Zheng, Guoyan
Subjects:	500 Science > 570 Life sciences; biology 600 Technology > 610 Medicine & health
ISBN:	978-1-4673-6456-0
Publisher:	IEEE
Language:	English
Submitter:	Guoyan Zheng
Date Deposited:	06 Jun 2014 16:55
Last Modified:	05 Dec 2022 14:31
Publisher DOI:	10.1109/ISBI.2013.6556762
URI:	https://boris.unibe.ch/id/eprint/46489