Knowledge-Driven Formalization of Laparoscopic Surgeries for Rule-Based Intraoperative Context-Aware Assistance

Katić, Darko; Wekerle, Anna-Laura; Gärtner, Fabian; Kenngott, Hannes; Müller‐Stich, Beat P.; Dillmann, Rüdiger; Speidel, Stefanie

doi:10.1007/978-3-319-07521-1_17

Cited by 32 publications

(39 citation statements)

References 22 publications

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“…Their use offers interoperability and easier integration of other ontologies making LapOntoSPM extendable and useful in a multitude of use cases. In contrast to the ontology used in [24], LapOntoSPM has a wider scope. It is not only built for the particular purpose of surgical phase recognition but meant to represent entire models of surgical workflows.…”

Section: Introductionmentioning

confidence: 94%

“…We developed an ontology-based situation interpretation system for laparoscopy [24]. It consists of two components: an ontology for laparoscopic knowledge and a situation interpretation algorithm.…”

Section: Introductionmentioning

confidence: 99%

“…To evaluate its aptness for context awareness, we created a new formulation of the situation interpretation algorithm based on [24] to work with the new ontology. The new algorithm matched the recognition rates of the previous one, proving that no interpretation ability was compromised in comparison with a fully customized, problem-specific knowledge representation.…”

Section: Introductionmentioning

confidence: 99%

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LapOntoSPM: an ontology for laparoscopic surgeries and its application to surgical phase recognition

et al. 2015

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We successfully integrated medical knowledge for laparoscopic surgeries into OntoSPM, facilitating knowledge and data sharing. This is especially important for reproducibility of results and unbiased comparison of recognition algorithms. The associated recognition algorithm was adapted to the new representation without any loss of classification power. The work is an important step to standardized knowledge and data representation in the field on context awareness and thus toward unified benchmark data sets.

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Section: Introductionmentioning

confidence: 94%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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LapOntoSPM: an ontology for laparoscopic surgeries and its application to surgical phase recognition

et al. 2015

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“…In the pertaining literature, context-dependent support is frequently mentioned as one of the chief objectives in the research field of SPMs [64][65][66][67][68]. However, these systems need to be intelligible and not overtaxing for their user(s) [69] as well as suitably balanced between proactivity and transparency [70].…”

Section: Spms For Workflow Management In the Ormentioning

confidence: 99%

Surgical process modeling

Neumuth

2017

Innovative Surgical Sciences

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Due to the rapidly evolving medical, technological, and technical possibilities, surgical procedures are becoming more and more complex. On the one hand, this offers an increasing number of advantages for patients, such as enhanced patient safety, minimal invasive interventions, and less medical malpractices. On the other hand, it also heightens pressure on surgeons and other clinical staff and has brought about a new policy in hospitals, which must rely on a great number of economic, social, psychological, qualitative, practical, and technological resources. As a result, medical disciplines, such as surgery, are slowly merging with technical disciplines. However, this synergy is not yet fully matured. The current information and communication technology in hospitals cannot manage the clinical and operational sequence adequately. The consequences are breaches in the surgical workflow, extensions in procedure times, and media disruptions. Furthermore, the data accrued in operating rooms (ORs) by surgeons and systems are not sufficiently implemented. A flood of information, "big data", is available from information systems. That might be deployed in the context of Medicine 4.0 to facilitate the surgical treatment. However, it is unused due to infrastructure breaches or communication errors. Surgical process models (SPMs) alleviate these problems. They can be defined as simplified, formal, or semiformal representations of a network of surgery-related activities, reflecting a predefined subset of interest. They can employ different means of generation, languages, and data acquisition strategies. They can represent surgical interventions with high resolution, offering qualifiable and quantifiable information on the course of the intervention on the level of single, minute, surgical work-steps. The basic idea is to gather information concerning the surgical intervention and its activities, such as performance time, surgical instrument used, trajectories, movements, or intervention phases. These data can be gathered by means of workflow recordings.These recordings are abstracted to represent an individual surgical process as a model and are an essential requirement to enable Medicine 4.0 in the OR. Further abstraction can be generated by merging individual process models to form generic SPMs to increase the validity for a larger number of patients. Furthermore, these models can be applied in a wide variety of use-cases. In this regard, the term "modeling" can be used to support either one or more of the following tasks: "to describe", "to understand", "to explain", to optimize", "to learn", "to teach", or "to automate". Possible use-cases are requirements analyses, evaluating surgical assist systems, generating surgeon-specific training-recommendation, creating workflow management systems for ORs, and comparing different surgical strategies. The presented chapter will give an introduction into this challenging topic, presenting different methods to generate SPMs from the workflow in the OR, as well as various...

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“…A fundamentally different approach is to use formal knowledge representation methods like ontologies that use rules and logical reasoning to derive the current state. For example, Katic et al use Description Logic in the OWL-standard (Web Ontology Language) [94,95,214].…”

Section: Context Awarenessmentioning

confidence: 99%

Content-based processing and analysis of endoscopic images and videos: A survey

Münzer

Schoeffmann

Böszörményi

2017

Multimed Tools Appl

106

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In recent years, digital endoscopy has established as key technology for medical screenings and minimally invasive surgery. Since then, various research communities with manifold backgrounds have picked up on the idea of processing and automatically analyzing the inherently available video signal that is produced by the endoscopic camera. Proposed works mainly include image processing techniques, pattern recognition, machine learning methods and Computer Vision algorithms. While most contributions deal with realtime assistance at procedure time, the post-procedural processing of recorded videos is still in its infancy. Many post-processing problems are based on typical Multimedia methods like indexing, retrieval, summarization and video interaction, but have only been sparsely addressed so far for this domain. The goals of this survey are (1) to introduce this research field to a broader audience in the Multimedia community to stimulate further research, (2) to describe domain-specific characteristics of endoscopic videos that need to be addressed in a pre-processing step, and (3) to systematically bring together the very diverse research results for the first time to provide a broader overview of related research that is currently not perceived as belonging together.

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Knowledge-Driven Formalization of Laparoscopic Surgeries for Rule-Based Intraoperative Context-Aware Assistance

Cited by 32 publications

References 22 publications

LapOntoSPM: an ontology for laparoscopic surgeries and its application to surgical phase recognition

LapOntoSPM: an ontology for laparoscopic surgeries and its application to surgical phase recognition

Surgical process modeling

Content-based processing and analysis of endoscopic images and videos: A survey

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