Title :
[POSTER] Deformation Estimation of Elastic Bodies Using Multiple Silhouette Images for Endoscopic Image Augmentation
Author :
Akira Saito;Megumi Nakao;Yuki Uranishi;Tetsuya Matsuda
Author_Institution :
Grad. Sch. of Inf., Kyoto Univ., Kyoto, Japan
Abstract :
This study proposes a method to estimate elastic deformation using silhouettes obtained from multiple endoscopic images. Our method can estimate the intraoperative deformation of organs using a volumetric mesh model reconstructed from preoperative CT data. We use this elastic body silhouette information of elastic bodies not to model the shape but to estimate the local displacements. The model shape is updated to satisfy the silhouette constraint while preserving the shape as much as possible. The result of the experiments showed that the proposed methods could estimate the deformation with root mean square (RMS) errors of 5.0–10 mm.
Keywords :
"Shape","Estimation","Deformable models","Surgery","Computed tomography","Augmented reality","Computational modeling"
Conference_Titel :
Mixed and Augmented Reality (ISMAR), 2015 IEEE International Symposium on
DOI :
10.1109/ISMAR.2015.49