Koo, B; Ozg ur, E; Le Roy, B; Buc, E; Bartoli, A; (2017) Deformable Registration of a Preoperative 3D Liver Volume to a Laparoscopy Image Using Contour and Shading Cues. In: Descoteaux, M and Maier-Hein, L and Franz, A and Jannin, P and Collins, DL and Duchesne, S, (eds.) Medical Image Computing and Computer Assisted Intervention − MICCAI 2017. (pp. pp. 326-334). Springer International Publishing: Cham, Switzerland.

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Abstract

The deformable registration of a preoperative organ volume to an intraoperative laparoscopy image is required to achieve augmented reality in laparoscopy. This is an extremely challenging objective for the liver. This is because the preoperative volume is textureless, and the liver is deformed and only partially visible in the laparoscopy image. We solve this problem by modeling the preoperative volume as a Neo-Hookean elastic model, which we evolve under shading and contour cues. The contour cues combine the organ’s silhouette and a few curvilinear anatomical landmarks. The problem is difficult because the shading cue is highly nonconvex and the contour cues give curve-level (and not point-level) correspondences. We propose a convergent alternating projections algorithm, which achieves a $$4%$$ registration error.

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