ISINet: An Instance-Based Approach for Surgical Instrument Segmentation-Reference-Cited by-同舟云学术

ISINet: An Instance-Based Approach for Surgical Instrument Segmentation

Published:2020 Issue: Volume: Page:595-605
ISSN:0302-9743
Container-title:Medical Image Computing and Computer Assisted Intervention – MICCAI 2020
language:
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Author:

González Cristina^ORCID,Bravo-Sánchez Laura^ORCID,Arbelaez Pablo^ORCID

Publisher

Springer International Publishing

Link

https://link.springer.com/content/pdf/10.1007/978-3-030-59716-0_57

Reference32 articles.

1. Allan, M., et al.: 2018 robotic scene segmentation challenge. arXiv preprint arXiv:2001.11190 (2020)

2. Allan, M., et al.: 2017 robotic instrument segmentation challenge. arXiv preprint arXiv:1902.06426 (2019)

3. Bodenstedt, S., et al.: Comparative evaluation of instrument segmentation and tracking methods in minimally invasive surgery. arXiv preprint arXiv:1805.02475 (2018)

4. Bouget, D., Benenson, R., Omran, M., Riffaud, L., Schiele, B., Jannin, P.: Detecting surgical tools by modelling local appearance and global shape. IEEE Trans. Med. Imaging 34(12), 2603–2617 (2015)

5. Lecture Notes in Computer Science;DJ Butler,2012

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