5 citations · 8 across the 7 of their papers we have counts for
3 papers · 1 filter
IGCN: Image-to-graph Convolutional Network for 2D/3D Deformable Registration
Megumi Nakao, Mitsuhiro Nakamura, Tetsuya Matsuda
Organ shape reconstruction based on a single-projection image during treatment has wide clinical scope, e.g., in image-guided radiotherapy and surgical guidance. We propose an imag…
Image-to-Graph Convolutional Network for Deformable Shape Reconstruction from a Single Projection Image
M. Nakao, F. Tong, M. Nakamura +1
Shape reconstruction of deformable organs from two-dimensional X-ray images is a key technology for image-guided intervention. In this paper, we propose an image-to-graph convoluti…
Kernel-based framework to estimate deformations of pneumothorax lung using relative position of anatomical landmarks
Utako Yamamoto, Megumi Nakao, Masayuki Ohzeki +3
In video-assisted thoracoscopic surgeries, successful procedures of nodule resection are highly dependent on the precise estimation of lung deformation between the inflated lung in…