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IVAP 2025 - Towards the collaborative operating room

DOI 10.18127/j15604136-2018007-15

Keywords:

D. Ostler - Research Group MITI, Klinikum rechts der Isar, Technical University Munich, Trogerstr. 26, 81675 Munich, Germany

N. Marahrens - Huawei Munich Research Centre, Germany

N. Kohn - Huawei Munich Research Centre, Germany

S. Koller - Huawei Munich Research Centre, Germany

M. Kranzfelder - Huawei Munich Research Centre, Germany; Department of Surgery, Klinikum rechts der Isar, Technical University Munich, Ismaninger Str. 22, 81675 Munich, Germany

H. Feussner  - Huawei Munich Research Centre, Germany; Department of Surgery, Klinikum rechts der Isar, Technical University Munich, Ismaninger Str. 22, 81675 Munich, Germany

D. Wilhelm  - Huawei Munich Research Centre, Germany; Department of Surgery, Klinikum rechts der Isar, Technical University Munich, Ismaninger Str. 22, 81675 Munich, Germany


The advances in digitalization and information processing  are influencing interventional medicine. Medical  devices include a growing number of functionalities, which  provide more operational flexibility while increasing complexity  of the OR environment [1]. Adapting to this development  provides an essential challenge and opportunity to  optimize modern surgery and therapy procedures. With the  advancements of digital assistance systems, it can be ensured  that the surgeon concentrates on the essential,  namely the patient and the operation, rather than being distracted  by the technical overflow of peripheral devices. In  this work we present our vision and first results of a collaborative  operating room that actively supports contextsensitive  intra- and postoperative surgical therapy. To  achieve this goal we enhanced a new Operating Room  (OR) for comprehensive data acquisition, recognition of  the OR team and computational tools for workflow analysis  in order to achieve an understanding of the situational  sequence and semi-automatic assistance and ensure an increased  security level.  The functioning of the cognitive surgical environment is  demonstrated by a typical example: the laparoscopic resection  of the gallbladder for symptomatic gallstones. Such an  operation is very common and is performed about 200,000  times a year in Germany. The procedure is highly standardized

References:
  1.  Kenngott H, Wagner M, Preukschas A et al. Der intelligente  Operationssaal. Der Chirurg 87:1033-1038, 2016. 
  2. Ostler D, Kranzfelder M, Stauder R et al. A centralized data  acquisition framework for operating theatres. In: E-health  Networking, Application & Services (HealthCom), 17th International  Conference on. IEEE, p 1-5, 2015. 
  3. Stauder R, Ostler D, Kranzfelder M et al. The TUM LapChole  dataset for the M2CAI 2016 workflow challenge. arXiv preprint  arXiv:1610.09278, 2016 
  4. Marahrens N, Koller S, Ostler D et al. Deep learning-based  robotic endoscope guidance. In: Jahrestagung CURAC, 2017. 
  5. Kranzfelder M, Schneider A, Fiolka A et al. Reliability of  sensor-based real-time workflow recognition in laparoscopic  cholecystectomy. International journal of computer assisted  radiology and surgery 9:941-948, 2014. 
  6. Feussner H, Ostler D, Kranzfelder M et al., Surgery 4.0. In  Health 4.0: How Virtualization and Big Data are Revolutionizing  Healthcare (pp. 91-107). Springer, Cham, 2017.

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