3D Imaging from Video and Planar Radiography

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9902)

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.

Notes

Acknowledgments

This research was partly funded by the KINOVIS project (ANR-11-EQPX-0024).

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Copyright information

© Springer International Publishing AG 2016

Authors and Affiliations

  1. 1.LJK, Inria GrenobleGrenobleFrance

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