Automated segmentation of phases, steps, and tasks in laparoscopic cholecystectomy using deep learning-Reference-Cited by-同舟云学术

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Automated segmentation of phases, steps, and tasks in laparoscopic cholecystectomy using deep learning

Published:2023-11-09 Issue:1 Volume:38 Page:158-170
ISSN:0930-2794
Container-title:Surgical Endoscopy
language:en
Short-container-title:Surg Endosc

Author:

Hegde Shruti R.,Namazi Babak,Iyengar Niyenth,Cao Sarah,Desir Alexis,Marques Carolina,Mahnken Heidi,Dumas Ryan P.,Sankaranarayanan Ganesh^ORCID

Funder

NH/NIBIB

Publisher

Springer Science and Business Media LLC

Subject

Surgery

Link

https://link.springer.com/content/pdf/10.1007/s00464-023-10482-3.pdf

Reference40 articles.

1. American Board of Surgery (2021) ABS to explore video-based assessment in pilot program launching, June 2021

2. Xu Z, Hu J, Deng W (2016) Recurrent convolutional neural network for video classification. In: 2016 IEEE international conference on multimedia & expo (ICME), pp. 1–6

3. Tran D et al (2015) Learning spatiotemporal features with 3D convolutional networks. In: 2015 IEEE international conference on computer vision (ICCV), pp 4489–4497

4. Wang LM et al (2016) Temporal segment networks: towards good practices for deep action recognition. Comput Vis 9912:20–36

5. Lam K et al (2022) Machine learning for technical skill assessment in surgery: a systematic review. NPJ Digit Med 5:1

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2. Artificial intelligence for improving intraoperative surgical care;Global Surgical Education - Journal of the Association for Surgical Education;2024-06-20

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