Surgical Workflow Recognition: From Analysis of Challenges to Architectural Study

Tobias Czempiel; Aidean Sharghi; Magdalini Paschali; Nassir Navab; Omid Mohareri

doi:10.1007/978-3-031-25066-8_32

Surgical Workflow Recognition: From Analysis of Challenges to Architectural Study

Tobias Czempiel, Aidean Sharghi, Magdalini Paschali, Nassir Navab, Omid Mohareri

Informatics 16 - Chair of Computer Aided Medical Procedures

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

2 Scopus citations

Abstract

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 operating room (OR) scene. In this work, we evaluate the performance of different combinations of common architectures for the task of surgical workflow recognition to provide a fair and comprehensive comparison of the methods for both settings, Internal and External. We show that the methods particularly designed for one setting can be transferred to the other mode and discuss the architecture effectiveness considering the main challenges for both Internal and External surgical workflow recognition.

Original language	English
Title of host publication	Computer Vision – ECCV 2022 Workshops, Proceedings
Editors	Leonid Karlinsky, Tomer Michaeli, Ko Nishino
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	556-568
Number of pages	13
ISBN (Print)	9783031250651
DOIs	https://doi.org/10.1007/978-3-031-25066-8_32
State	Published - 2023
Event	17th European Conference on Computer Vision, ECCV 2022 - Tel Aviv, Israel Duration: 23 Oct 2022 → 27 Oct 2022

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	13803 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	17th European Conference on Computer Vision, ECCV 2022
Country/Territory	Israel
City	Tel Aviv
Period	23/10/22 → 27/10/22

Keywords

Analysis
Benchmarking
Cholecystectomy
Concept ablation
Surgical phase recognition
Surgical workflow analysis

Access to Document

10.1007/978-3-031-25066-8_32

Cite this

Czempiel, T., Sharghi, A., Paschali, M., Navab, N., & Mohareri, O. (2023). Surgical Workflow Recognition: From Analysis of Challenges to Architectural Study. In L. Karlinsky, T. Michaeli, & K. Nishino (Eds.), Computer Vision – ECCV 2022 Workshops, Proceedings (pp. 556-568). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 13803 LNCS). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-031-25066-8_32

Czempiel, Tobias ; Sharghi, Aidean ; Paschali, Magdalini et al. / Surgical Workflow Recognition : From Analysis of Challenges to Architectural Study. Computer Vision – ECCV 2022 Workshops, Proceedings. editor / Leonid Karlinsky ; Tomer Michaeli ; Ko Nishino. Springer Science and Business Media Deutschland GmbH, 2023. pp. 556-568 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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title = "Surgical Workflow Recognition: From Analysis of Challenges to Architectural Study",

abstract = "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 operating room (OR) scene. In this work, we evaluate the performance of different combinations of common architectures for the task of surgical workflow recognition to provide a fair and comprehensive comparison of the methods for both settings, Internal and External. We show that the methods particularly designed for one setting can be transferred to the other mode and discuss the architecture effectiveness considering the main challenges for both Internal and External surgical workflow recognition.",

keywords = "Analysis, Benchmarking, Cholecystectomy, Concept ablation, Surgical phase recognition, Surgical workflow analysis",

author = "Tobias Czempiel and Aidean Sharghi and Magdalini Paschali and Nassir Navab and Omid Mohareri",

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Czempiel, T, Sharghi, A, Paschali, M, Navab, N & Mohareri, O 2023, Surgical Workflow Recognition: From Analysis of Challenges to Architectural Study. in L Karlinsky, T Michaeli & K Nishino (eds), Computer Vision – ECCV 2022 Workshops, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 13803 LNCS, Springer Science and Business Media Deutschland GmbH, pp. 556-568, 17th European Conference on Computer Vision, ECCV 2022, Tel Aviv, Israel, 23/10/22. https://doi.org/10.1007/978-3-031-25066-8_32

Surgical Workflow Recognition: From Analysis of Challenges to Architectural Study. / Czempiel, Tobias; Sharghi, Aidean; Paschali, Magdalini et al.
Computer Vision – ECCV 2022 Workshops, Proceedings. ed. / Leonid Karlinsky; Tomer Michaeli; Ko Nishino. Springer Science and Business Media Deutschland GmbH, 2023. p. 556-568 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 13803 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Navab, Nassir

AU - Mohareri, Omid

PY - 2023

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AB - 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 operating room (OR) scene. In this work, we evaluate the performance of different combinations of common architectures for the task of surgical workflow recognition to provide a fair and comprehensive comparison of the methods for both settings, Internal and External. We show that the methods particularly designed for one setting can be transferred to the other mode and discuss the architecture effectiveness considering the main challenges for both Internal and External surgical workflow recognition.

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T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

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Czempiel T, Sharghi A, Paschali M, Navab N, Mohareri O. Surgical Workflow Recognition: From Analysis of Challenges to Architectural Study. In Karlinsky L, Michaeli T, Nishino K, editors, Computer Vision – ECCV 2022 Workshops, Proceedings. Springer Science and Business Media Deutschland GmbH. 2023. p. 556-568. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-031-25066-8_32