Multiple reconstruction and dynamic modeling of 3D digital objects using a morphing approach

Application to kidney animation and tumor tracking


Organ segmentation and motion simulation of organs can be useful for many clinical purposes such as organ study, diagnostic aid, therapy planning or even tumor destruction. In this paper we present a full workflow starting from a CT-Scan resulting in kidney motion simulation and tumor tracking. Our method is divided into three major steps: kidney segmentation, surface reconstruction and animation. The segmentation is based on a semi-automatic region-growing approach that is refined to improve its results. The reconstruction is performed using the Poisson surface reconstruction and gives a manifold three-dimensional (3D) model of the kidney. Finally, the animation is accomplished using an automatic mesh morphing among the models previously obtained. Thus, the results are purely geometric because they are 3D animated models. Moreover, our method requires only a basic user interaction and is fast enough to be used in a medical environment, which satisfies our constraints. Finally, this method can be easily adapted to magnetic resonance imaging acquisition because only the segmentation part would require minor modifications.

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This work was granted by the group Novartis and by the Foundation “Santé, Sport et Développement Durable”, presided over Pr. Yvon Berland. The authors would like to thank the persons involved in the Kidney Tumor Tracking (KiTT) project: Christian Coulange for his precious help, Marc André, Frédéric Cohen Philippe Souteyrand and Julien Frandon for their wise advice and for providing CT scan data, and Pierre-Henri Rolland for his support.

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Correspondence to Valentin Leonardi.

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Leonardi, V., Vidal, V., Daniel, M. et al. Multiple reconstruction and dynamic modeling of 3D digital objects using a morphing approach. Vis Comput 31, 557–574 (2015).

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  • Geometric modeling
  • Surface reconstruction
  • Dynamic modeling
  • Mesh morphing