SAM 2 in Robotic Surgery: An Empirical Evaluation for Robustness and Generalization in Surgical Video Segmentation

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Shvets, A.A., Rakhlin, A., Kalinin, A.A., Iglovikov, V.I.: Automatic instrument segmentation in robot-assisted surgery using deep learning. In: 2018 17th IEEE International Conference on Machine Learning and Applications (ICMLA). pp. 624–628 (2018)

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2019

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Islam, M., Atputharuban, D.A., Ramesh, R., Ren, H.: Real-time instrument segmentation in robotic surgery using auxiliary supervised deep adversarial learning. IEEE Robotics and Automation Letters 4

2019

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Jin, Y., Cheng, K., Dou, Q., Heng, P.A.: Incorporating temporal prior from motion flow for instrument segmentation in minimally invasive surgery video. In: Medical Image Computing and Computer Assisted Intervention–MICCAI 2019: 22nd International Conference, Shenzhen, China, October 13–17, 2019, Proceedings, Part V 22. pp. 440–448. Springer (2019)

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Islam, M., Vibashan, V., Ren, H.: Ap-mtl: Attention pruned multi-task learning model for real-time instrument detection and segmentation in robot-assisted surgery. In: 2020 IEEE international conference on robotics and automation (ICRA). pp. 8433–8439. IEEE (2020)

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Pakhomov, D., Navab, N.: Searching for efficient architecture for instrument segmentation in robotic surgery. In: Medical Image Computing and Computer Assisted Intervention–MICCAI 2020: 23rd International Conference, Lima, Peru, October 4–8, 2020, Proceedings, Part III 23. pp. 648–656. Springer (2020)

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Hu, E.J., Shen, Y., Wallis, P., Allen-Zhu, Z., Li, Y., Wang, S., Wang, L., Chen, W.: Lora: Low-rank adaptation of large language models. arXiv preprint arXiv:2106.09685 (2021)

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2021

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Islam, M., Vibashan, V., Lim, C.M., Ren, H.: St-mtl: Spatio-temporal multitask learning model to predict scanpath while tracking instruments in robotic surgery. Medical Image Analysis 67

2021

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Seenivasan, L., Mitheran, S., Islam, M., Ren, H.: Global-reasoned multi-task learning model for surgical scene understanding. IEEE Robotics and Automation Letters 7

2022

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Wang, A., Islam, M., Xu, M., Ren, H.: Rethinking surgical instrument segmentation: A background image can be all you need. In: International Conference on Medical Image Computing and Computer-Assisted Intervention. pp. 355–364. Springer (2022)

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Ma, J., Wang, B.: Segment anything in medical images (2023)

2023

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Wang, A., Islam, M., Xu, M., Zhang, Y., Ren, H.: Sam meets robotic surgery: an empirical study on generalization, robustness and adaptation. In: International Conference on Medical Image Computing and Computer-Assisted Intervention. pp. 234–244. Springer (2023)

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Wang, G., Bai, L., Wu, Y., Chen, T., Ren, H.: Rethinking exemplars for continual semantic segmentation in endoscopy scenes: Entropy-based mini-batch pseudo-replay. Computers in Biology and Medicine 165

2023

Later among the works it cites.

Wu, J., Fu, R., Fang, H., Liu, Y., Wang, Z., Xu, Y., Jin, Y., Arbel, T.: Medical sam adapter: Adapting segment anything model for medical image segmentation. arXiv preprint arXiv:2304.12620 (2023)

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2023

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