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Tissue deformation poses a key challenge for accurate surgical scene reconstruction.
Rodby, K.A., Turin, S., Jacobs, R.J., Cruz, J.F., Hassid, V.J., Kolokythas, A., Antony, A.K.: Advances in oncologic head and neck reconstruction: systematic review and future considerations of virtual surgical planning and computer aided design/computer aided modeling. Journal of Plastic, Reconstructive & Aesthetic Surgery 67
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Schonberger, J.L., Frahm, J.M.: Structure-from-motion revisited. In: Proceedings of the IEEE conference on computer vision and pattern recognition. pp. 4104–4113 (2016)
2016
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Liu, X., Stiber, M., Huang, J., Ishii, M., Hager, G.D., Taylor, R.H., Unberath, M.: Reconstructing sinus anatomy from endoscopic video–towards a radiation-free approach for quantitative longitudinal assessment. In: Medical Image Computing and Computer Assisted Intervention–MICCAI 2020: 23rd International Conference, Lima, Peru, October 4–8, 2020, Proceedings, Part III 23. pp. 3–13. Springer (2020)
2020
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Boedecker, C., Huettl, F., Saalfeld, P., Paschold, M., Kneist, W., Baumgart, J., Preim, B., Hansen, C., Lang, H., Huber, T.: Using virtual 3d-models in surgical planning: workflow of an immersive virtual reality application in liver surgery. Langenbeck’s archives of surgery 406
2021
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Imambi, S., Prakash, K.B., Kanagachidambaresan, G.: Pytorch. Programming with TensorFlow: Solution for Edge Computing Applications pp. 87–104 (2021)
2021
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Mildenhall, B., Srinivasan, P.P., Tancik, M., Barron, J.T., Ramamoorthi, R., Ng, R.: Nerf: Representing scenes as neural radiance fields for view synthesis. Communications of the ACM 65
2021
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Pelanis, E., Teatini, A., Eigl, B., Regensburger, A., Alzaga, A., Kumar, R.P., Rudolph, T., Aghayan, D.L., Riediger, C., Kvarnström, N., et al.: Evaluation of a novel navigation platform for laparoscopic liver surgery with organ deformation compensation using injected fiducials. Medical image analysis 69
2021
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Wang, Y., Long, Y., Fan, S.H., Dou, Q.: Neural rendering for stereo 3d reconstruction of deformable tissues in robotic surgery. In: International Conference on Medical Image Computing and Computer-Assisted Intervention. pp. 431–441. Springer (2022)
2022
Cited alongside, same era.
Cao, A., Johnson, J.: Hexplane: A fast representation for dynamic scenes. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 130–141 (2023)
2023
Cited alongside, same era.
Hayoz, M., Hahne, C., Gallardo, M., Candinas, D., Kurmann, T., Allan, M., Sznitman, R.: Learning how to robustly estimate camera pose in endoscopic videos. International journal of computer assisted radiology and surgery 18
2023
Cited alongside, same era.
Kerbl, B., Kopanas, G., Leimkühler, T., Drettakis, G.: 3d gaussian splatting for real-time radiance field rendering. ACM Transactions on Graphics 42
2023
Cited alongside, same era.
2023
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Wu, T.Y., Meng, Q., Yang, L., Kumari, S., Pirouz, M.: Amassing the security: An enhanced authentication and key agreement protocol for remote surgery in healthcare environment. CMES-Computer Modeling in Engineering & Sciences 134
2023
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2023
Later among the works it cites.
2023
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2023
Cited alongside, same era.
2023
Cited alongside, same era.
2023
Cited alongside, same era.
Zha, R., Cheng, X., Li, H., Harandi, M., Ge, Z.: Endosurf: Neural surface reconstruction of deformable tissues with stereo endoscope videos. In: International Conference on Medical Image Computing and Computer-Assisted Intervention. pp. 13–23. Springer (2023)
2023
Later among the works it cites.
Liu, Y., Li, C., Yang, C., Yixuan, Y.: Endogaussian: Gaussian splatting for deformable surgical scene reconstruction. Arxiv (2024)
2024
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