20 March 2018 Develop and validate a finite element method model for deformation matching of laparoscopic gastrectomy navigation
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Abstract
Experimental surgical navigation systems have been reported being used in laparoscopic surgery, however, accurate registration in the surgical navigation is very challenging due to vessel deformation. We aim to build a deformable model based on the preoperative CT images to improve the matching accuracy by using the finite element method (FEM). Enhanced CT scans before and after the left gastric artery (LGA) pulled up were performed for FEM model and ground-truth generating in a pig experiment, respectively. An ANSYS software was used to simulate the FEM model of the vessel after pulled up according to the need for the laparoscopic gastrectomy. The central line (Line B) of the FEM model and central line (Line A) of the ground-truth were drawn and compared with each other. On the basis of material and parameters acquired from the animal experiment, we built a perigastric vessels FEM model of the patient with gastric cancer and evaluated its accuracy in surgical scene of laparoscopic gastrectomy. In animal experiment, the average distance between the two central lines is 6.467mm while the average distance between the closest points of them is 3.751mm. In surgical scene of laparoscopic gastrectomy, superimposing the FEM model onto the 2D laparoscopic image demonstrated a good coincidence. In this study, we built a deformable vessel model based on the preoperative CT images which may improve the matching accuracy and supply a referable way for further research of the deformation matching in the laparoscopic gastrectomy navigation.
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Tao Chen, Tao Chen, Guodong Wei, Guodong Wei, Weili Shi, Weili Shi, Yuichiro Hayashi, Yuichiro Hayashi, Masahiro Oda, Masahiro Oda, Zhengang Jiang, Zhengang Jiang, Guoxin Li, Guoxin Li, Kensaku Mori, Kensaku Mori, } "Develop and validate a finite element method model for deformation matching of laparoscopic gastrectomy navigation", Proc. SPIE 10576, Medical Imaging 2018: Image-Guided Procedures, Robotic Interventions, and Modeling, 105761Y (20 March 2018); doi: 10.1117/12.2293288; https://doi.org/10.1117/12.2293288
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