OntoFlow, a software tool for surgical workflow recording

Nagy, Dénes Ákos; Rudas, Imre J.; Haidegger, Tamás

doi:10.1109/sami.2018.8323998

Cited by 6 publications

(3 citation statements)

References 11 publications

(9 reference statements)

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“…A possible solution could be the use of a specialized software such as the SWAN-Suite (59), which has proven to be highly accurate when registering and analyzing surgical workflows in several institutions. There exist other video-based algorithms (60)(61)(62) that could help in improving the labeling accuracy of the SPM creation process. However, most of the recent datadriven surgical activity recognition methods rely on a proper understanding of a model that describes the underlying surgical 'process'; therefore, the presented SPMs in this study can serve as the basis for the development of such algorithms that can be used in open spinal surgery applications.…”

Section: Discussionmentioning

confidence: 99%

Surgical Process Modeling for Open Spinal Surgeries

Carrillo

Esfandiari²,

Muller³

et al. 2022

Front. Surg.

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Modern operating rooms are becoming increasingly advanced thanks to the emerging medical technologies and cutting-edge surgical techniques. Current surgeries are transitioning into complex processes that involve information and actions from multiple resources. When designing context-aware medical technologies for a given intervention, it is of utmost importance to have a deep understanding of the underlying surgical process. This is essential to develop technologies that can correctly address the clinical needs and can adapt to the existing workflow. Surgical Process Modeling (SPM) is a relatively recent discipline that focuses on achieving a profound understanding of the surgical workflow and providing a model that explains the elements of a given surgery as well as their sequence and hierarchy, both in quantitative and qualitative manner. To date, a significant body of work has been dedicated to the development of comprehensive SPMs for minimally invasive baroscopic and endoscopic surgeries, while such models are missing for open spinal surgeries. In this paper, we provide SPMs common open spinal interventions in orthopedics. Direct video observations of surgeries conducted in our institution were used to derive temporal and transitional information about the surgical activities. This information was later used to develop detailed SPMs that modeled different primary surgical steps and highlighted the frequency of transitions between the surgical activities made within each step. Given the recent emersion of advanced techniques that are tailored to open spinal surgeries (e.g., artificial intelligence methods for intraoperative guidance and navigation), we believe that the SPMs provided in this study can serve as the basis for further advancement of next-generation algorithms dedicated to open spinal interventions that require a profound understanding of the surgical workflow (e.g., automatic surgical activity recognition and surgical skill evaluation). Furthermore, the models provided in this study can potentially benefit the clinical community through standardization of the surgery, which is essential for surgical training.

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Section: Discussionmentioning

confidence: 99%

Surgical Process Modeling for Open Spinal Surgeries

Carrillo

Esfandiari²,

Muller³

et al. 2022

Front. Surg.

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“…Currently, two proprietary products are available to record surgical workflows, The SWAN Suite (Innovation Center Computer-Assisted Surgery, Universitaat Leipzig) [13], and the b<>com software [14] (University of Rennes and the Institute of Research and Technology). In our previous work, we also presented the OntoFlow software, a java-based solution providing direct integration of ontology development and process recording [15]. While all three software have a good range of functionality, we decided to opt for a web based solution to reach out to more students by providing an easily accessible platform.…”

Section: Software Architecturementioning

confidence: 99%

Employing Process Models for Surgical Training

Nagy

Takacs

Rudas

et al. 2020

2020 IEEE 18th World Symposium on Applied Machine Intelligence and Informatics (SAMI)

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The exponential rise in minimally invasive procedures throughout the last three decades shifted the focus from individual manual skills to complex engineering solutions. To streamline the delivery of these novel techniques, Surgical Process Models (SPMs) have been under development. SPMs provide the basis for machine learning algorithms to frame the surgical procedure and anchor themselves into the workflow. Process recording is an essential tool to create an accurate representation of the SPM. Process recording, continued with human expert evaluation have been used to assess operator skills and compare interventional approaches. In this paper, we present a web-based surgical process recording tool which is evaluated in a surgical training scenario. Our aim is to involve the trainees in process recording, therefore actively exploring the generic process model of laparoscopic cholecystectomy. Along with training we also use the process records to identify the most accurately represented time points of process transitions, therefore providing target events for future monitoring systems.

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“…The surgical workflow of RAS procedures often contains time-consuming and monotonous elements-so-called surgical subtasks-like suturing, knot-tying, or blunt dissection. The automation of these subtasks can reduce the fatigue and the cognitive load on the surgeon, who can hence pay more attention to the more critical parts of the intervention [6].…”

Section: Subtask Automation In Surgerymentioning

confidence: 99%

A DVRK-based Framework for Surgical Subtask Automation

2019

APH

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Robotic assistance is becoming a standard in Minimally Invasive Surgery. Despite its clinical benefits and technical potential, surgeons still have to perform manually a number of monotonous and time-consuming surgical subtasks, like knot-tying or blunt dissection. Many believe that the next bold step in the advancement of robotic surgery is the automation of such subtasks. Partial automation can reduce the cognitive load on surgeons, and support them in paying more attention to the critical elements of the surgical workflow. Our aim was to develop a software framework to ease and hasten the automation of surgical subtasks. This framework was built alongside the Da Vinci Research Kit (DVRK), while it can be ported onto other robotic platforms, since it is based on the Robot Operating System (ROS). The software includes both stereo vision-based and hierarchical motion planning, with a wide palette of often used surgical gestures-such as grasping, cutting or soft tissue manipulation-as building blocks to support the high-level implementation of autonomous surgical subtask execution routines. This open-source surgical automation framework-named irob-saf-is available at https://github.com/ABC-iRobotics/irob-saf.

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OntoFlow, a software tool for surgical workflow recording

Cited by 6 publications

References 11 publications

Surgical Process Modeling for Open Spinal Surgeries

Surgical Process Modeling for Open Spinal Surgeries

Employing Process Models for Surgical Training

A DVRK-based Framework for Surgical Subtask Automation

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