CT from Motion: Volumetric Capture of Moving Shapes using X-rays

Julien Pansiot and Edmond Boyer

Abstract

In this paper, we consider the capture of dense volumetric X-ray attenuation models of non-rigidly moving samples. Traditional 3D medical imaging apparatus, e.g. CT or MRI, do not easily adapt to shapes that deform significantly such as a moving hand. We propose an approach that simultaneously recovers dense volumetric shape and motion information by combining video and X-ray modalities. Multiple colour images are captured to track shape surfaces while a single X-ray device is used to infer inner attenuations. The approach does not assume prior models which makes it versatile and easy to generalise over different shapes. Results on synthetic and real-life data are presented that demonstrate the approach feasibility with a limited number of X-ray views.

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DOI

10.5244/C.31.26
https://dx.doi.org/10.5244/C.31.26

Citation

Julien Pansiot and Edmond Boyer. CT from Motion: Volumetric Capture of Moving Shapes using X-rays. In T.K. Kim, S. Zafeiriou, G. Brostow and K. Mikolajczyk, editors, Proceedings of the British Machine Vision Conference (BMVC), pages 26.1-26.12. BMVA Press, September 2017.

Bibtex

            @inproceedings{BMVC2017_26,
                title={CT from Motion: Volumetric Capture of Moving Shapes using X-rays},
                author={Julien Pansiot and Edmond Boyer},
                year={2017},
                month={September},
                pages={26.1-26.12},
                articleno={26},
                numpages={12},
                booktitle={Proceedings of the British Machine Vision Conference (BMVC)},
                publisher={BMVA Press},
                editor={Tae-Kyun Kim, Stefanos Zafeiriou, Gabriel Brostow and Krystian Mikolajczyk},
                doi={10.5244/C.31.26},
                isbn={1-901725-60-X},
                url={https://dx.doi.org/10.5244/C.31.26}
            }