2015
DOI: 10.1007/s11548-015-1222-1
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LapOntoSPM: an ontology for laparoscopic surgeries and its application to surgical phase recognition

Abstract: 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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Cited by 59 publications
(44 citation statements)
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“…The general idea of our approach is to represent the surgical workflow using an ontology, namely LapOntoSPM [23], at the granularity level of activities. The goal is to infer the surgical phase based on this model.…”
Section: Methodsmentioning
confidence: 99%
See 2 more Smart Citations
“…The general idea of our approach is to represent the surgical workflow using an ontology, namely LapOntoSPM [23], at the granularity level of activities. The goal is to infer the surgical phase based on this model.…”
Section: Methodsmentioning
confidence: 99%
“…These rules are accessible to human understanding and can be verified and extended as necessary. We define rules using so-called Triggering Activities [23]. Triggering Activities are activities which are indicative of the beginning of a phase.…”
Section: Combination Of Formal and Experience-based Knowledge For Phamentioning
confidence: 99%
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“…To achieve this goal the OntoSPM international group was formed. The ontology developed by this group (also called OntoSPM) is based on the Basic Formal Ontology (BFO) upper ontology [18], and provides a connection to more specified ontologies, such as LapOntoSPM [19], [20].…”
Section: Ontologymentioning
confidence: 99%
“…Analysis of these data can reveal behavioural patterns, which we call the surgical workflow. With the use of intelligent algorithms, a model can be built to autonomously detect and identify different steps in the surgical procedure [6]. Through recognition of different phases during a procedure, we can also estimate how long the procedure will take and thus optimise our schedule.…”
mentioning
confidence: 99%