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Conference Papers Year : 2016

3D Imaging from Video and Planar Radiography

(1) , (1)
1
Julien Pansiot
Edmond Boyer

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.
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Format : Video
Origin : Files produced by the author(s)
Format : Figure, Image
Origin : Files produced by the author(s)
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Dates and versions

hal-01348939 , version 1 (19-09-2016)
hal-01348939 , version 2 (24-10-2016)

Licence

Attribution - NonCommercial - NoDerivatives - CC BY 4.0

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Julien Pansiot, Edmond Boyer. 3D Imaging from Video and Planar Radiography. MICCAI 2016 - 19th International Conference on Medical Image Computing and Computer Assisted Intervention, Oct 2016, Athens, Greece. pp.450-457, ⟨10.1007/978-3-319-46726-9_52⟩. ⟨hal-01348939v2⟩
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