Computer Science > Computer Vision and Pattern Recognition
arXiv:2203.09230 (cs)
[Submitted on 17 Mar 2022 (v1), last revised 23 Nov 2022 (this version, v3)]
Title:Surgical Workflow Recognition: from Analysis of Challenges to Architectural Study
View a PDF of the paper titled Surgical Workflow Recognition: from Analysis of Challenges to Architectural Study, by Tobias Czempiel and 4 other authors
View PDFAbstract:Algorithmic surgical workflow recognition is an ongoing research field and can be divided into laparoscopic (Internal) and operating room (External) analysis. So far many different works for the internal analysis have been proposed with the combination of a frame-level and an additional temporal model to address the temporal ambiguities between different workflow phases. For the External recognition task, Clip-level methods are in the focus of researchers targeting the local ambiguities present in the OR scene. In this work we evaluate combinations of different model architectures for the task of surgical workflow recognition to provide a fair comparison of the methods for both Internal and External analysis. We show that methods designed for the Internal analysis can be transferred to the external task with comparable performance gains for different architectures.
| Comments: | 11 pages, 2 figures |
| Subjects: | Computer Vision and Pattern Recognition (cs.CV) |
| Cite as: | arXiv:2203.09230 [cs.CV] |
| (orarXiv:2203.09230v3 [cs.CV] for this version) | |
| https://doi.org/10.48550/arXiv.2203.09230 arXiv-issued DOI via DataCite | |
| Journal reference: | european conference on computer vision, ECCV 2022; MCV |
Submission history
From: Tobias Czempiel [view email][v1] Thu, 17 Mar 2022 10:36:48 UTC (568 KB)
[v2] Wed, 24 Aug 2022 07:38:58 UTC (2,057 KB)
[v3] Wed, 23 Nov 2022 18:24:26 UTC (2,057 KB)
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View a PDF of the paper titled Surgical Workflow Recognition: from Analysis of Challenges to Architectural Study, by Tobias Czempiel and 4 other authors
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