title: Surface reconstruction for planning and navigation of liver resections.
abstract: Computer-assisted systems for planning and navigation of liver resection procedures rely on the use of patient-specific 3D geometric models obtained from computed tomography. In this work, we propose the application of Poisson surface reconstruction (PSR) to obtain 3D models of the liver surface with applications to planning and navigation of liver surgery. In order to apply PSR, the introduction of an efficient transformation of the segmentation data, based on computation of gradient fields, is proposed. One of the advantages of PSR is that it requires only one control parameter, allowing the process to be fully automatic once the optimal value is estimated. Validation of our results is performed via comparison with 3D models obtained by state-of-art Marching Cubes incorporating Laplacian smoothing and decimation (MCSD). Our results show that PSR provides smooth liver models with better accuracy/complexity trade-off than those obtained by MCSD. After estimating the optimal parameter, automatic reconstruction of liver surfaces using PSR is achieved keeping similar processing time as MCSD. Models from this automatic approach show an average reduction of 79.59% of the polygons compared to the MCSD models presenting similar smoothness properties. Concerning visual quality, on one hand, and despite this reduction in polygons, clinicians perceive the quality of automatic PSR models to be the same as complex MCSD models. On the other hand, clinicians perceive a significant improvement on visual quality for automatic PSR models compared to optimal (obtained in terms of accuracy/complexity) MCSD models. The median reconstruction error using automatic PSR was as low as 1.03±0.23mm, which makes the method suitable for clinical applications. Automatic PSR is currently employed at Oslo University Hospital to obtain patient-specific liver models in selected patients undergoing laparoscopic liver resection.
authors.affiliation: Norwegia Media Technology Lab, Faculty of Computer Science and Media Technology, NTNU, Teknologivegen 22, 2815 Gjøvik, Norway; The Intervention Centre, Oslo University Hospital, P.O. box 4950 - Nydalen, 0424 Oslo, Norway; Faculty of Medicine, University of Oslo, 0372 Oslo, Norway. Electronic address: rafael.palomar@ntnu.no.
authors.forename: Rafael
authors.initials: R
authors.lastname: Palomar
authors.affiliation: Norwegia Media Technology Lab, Faculty of Computer Science and Media Technology, NTNU, Teknologivegen 22, 2815 Gjøvik, Norway; Faculty of Medicine, University of Oslo, 0372 Oslo, Norway.
authors.forename: Faouzi A
authors.initials: FA
authors.lastname: Cheikh
authors.affiliation: The Intervention Centre, Oslo University Hospital, P.O. box 4950 - Nydalen, 0424 Oslo, Norway; Faculty of Medicine, University of Oslo, 0372 Oslo, Norway.
authors.forename: Bjørn
authors.initials: B
authors.lastname: Edwin
authors.affiliation: L2TI, Institut Galilée, Université Paris 13, Avenue J. B. Clément 99, 93430 Villetaneuse, France; Faculty of Medicine, University of Oslo, 0372 Oslo, Norway.
authors.forename: Azeddine
authors.initials: A
authors.lastname: Beghdadhi
authors.affiliation: The Intervention Centre, Oslo University Hospital, P.O. box 4950 - Nydalen, 0424 Oslo, Norway; Department of Informatics, University of Oslo, 0373 Oslo, Norway; Faculty of Medicine, University of Oslo, 0372 Oslo, Norway.
authors.forename: Ole J
authors.initials: OJ
authors.lastname: Elle
mesh_terms: D006498:Hepatectomy; D006801:Humans; D008099:Liver / Q000000981:diagnostic imaging* / Q000601:surgery; D014057:Tomography, X-Ray Computed
keywords: Liver resection; Marching Cubes; Navigation; Planning; Poisson; Reconstruction; Surface modeling; Visualization