2D/3D deformable registration for endoscopic camera images using self-supervised offline learning of intraoperative pneumothorax deformation-Reference-Cited by-同舟云学术

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2D/3D deformable registration for endoscopic camera images using self-supervised offline learning of intraoperative pneumothorax deformation

Published:2024-09 Issue: Volume:116 Page:102418
ISSN:0895-6111
Container-title:Computerized Medical Imaging and Graphics
language:en
Short-container-title:Computerized Medical Imaging and Graphics

Author:

Oya Tomoki,Kadomatsu Yuka,Chen-Yoshikawa Toyofumi Fengshi,Nakao Megumi^ORCID

Funder

Japan Society for the Promotion of Science

Publisher

Elsevier BV

Reference46 articles.

1. Adagolodjo, Y., Trivisonne, R., Haouchine, N., Cotin, S., Courtecuisse, H., 2017. Silhouette-based pose estimation for deformable organs application to surgical augmented reality. In: 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems. IROS, pp. 539–544.

2. Use of image registration and fusion algorithms and techniques in radiotherapy: Report of the AAPM radiation therapy committee task group no. 132;Brock;Med. Phys.,2017

3. Brunet, J.N., Mendizabal, A., Petit, A., Golse, N., Vibert, E., Cotin, S., 2019. Physics-based deep neural network for augmented reality during liver surgery. In: International Conference on Medical Image Computing and Computer Assisted Intervention. MICCAI, pp. 137–145.

4. Augmented environments for the targeting of hepatic lesions during image-guided robotic liver surgery;Buchs;J. Surg. Res.,2013

5. 2D/3D non-rigid image registration via two orthogonal X-ray projection images for lung tumor tracking;Dong;Bioengineering,2023

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