SSIS-Seg: Simulation-Supervised Image Synthesis for Surgical Instrument Segmentation

Author:

Colleoni Emanuele1ORCID,Psychogyios Dimitris1ORCID,Van Amsterdam Beatrice1ORCID,Vasconcelos Francisco1ORCID,Stoyanov Danail1ORCID

Affiliation:

1. Wellcome/EPSRC Centre for Interventional and Surgical Sciences (WEISS), University College London (UCL), London, U.K.

Funder

Wellcome/ Engineering and Physical Sciences Research Council (EPSRC) Centre for Interventional and Surgical Sciences

EPSRC

Royal Academy of Engineering Chair in Emerging Technologies Scheme

Horizon 2020 Future and Emerging Technologies

Intuitive Surgical Inc.

daVinci Research Kit (dVRK) Community

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Computer Science Applications,Radiological and Ultrasound Technology,Software

Cited by 6 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Methods and datasets for segmentation of minimally invasive surgical instruments in endoscopic images and videos: A review of the state of the art;Computers in Biology and Medicine;2024-02

2. Structural and Pixel Relation Modeling for Semisupervised Instrument Segmentation From Surgical Videos;IEEE Transactions on Instrumentation and Measurement;2024

3. InstrumentNet: An integrated model for real-time segmentation of intracranial surgical instruments;Computers in Biology and Medicine;2023-11

4. Generalizing Surgical Instruments Segmentation to Unseen Domains with One-to-Many Synthesis;2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS);2023-10-01

5. Automated Microsurgical Tool Categorization using a Surface-Based EMG System;2023 45th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC);2023-07-24

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