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Erschienen in:
2016 | OriginalPaper | Buchkapitel
3D Imaging from Video and Planar Radiography
verfasst von : Julien Pansiot, Edmond Boyer
Erschienen in: Medical Image Computing and Computer-Assisted Intervention - MICCAI 2016
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Abstract
In this paper we consider dense volumetric modeling of moving samples such as body parts. Most dense modeling methods consider samples observed with a moving X-ray device and cannot easily handle moving samples. We propose a novel method that uses a surface motion capture system associated to a single low-cost/low-dose planar X-ray imaging device for dense in-depth attenuation information. Our key contribution is to rely on Bayesian inference to solve for a dense attenuation volume given planar radioscopic images of a moving sample. The approach enables multiple sources of noise to be considered and takes advantage of limited prior information to solve an otherwise ill-posed problem. Results show that the proposed strategy is able to reconstruct dense volumetric attenuation models from a very limited number of radiographic views over time on simulated and in-vivo data.