I01: Knowledge Modelling and Interpretation

The project "Knowledge Modelling and Interpretation" aims to develop a semantic knowledge base that models experience-based knowledge of the different subprojects by means of therapy plans, operation workflows and medical background knowledge. The aim is to develop a contextually aware assistance in pre- and intraoperative scenarios via the integration of these different data sources and self-learning interpretation algorithms. The project provides a standard for modelling, interpreting and communicating the patient’s individual anatomy, pathology and therapy.

Project Leaders

Prof. Dr.-Ing.
Rüdiger Dillmann

PD Dr. med.
Arianeb Mehrabi

Prof. Dr. rer. nat.
Rudi Studer


Our Team


Fetzer A, Metzger J, Katic D, März K, Wagner M et al.

"Toward an open-source semantic data infrastructure for integrating clinical and scientific data in cognition-guided surgery."

SPIE Medical Imaging 2016 (accepted).

Kaiser P, Lewis M, Petrick RPA, Asfour T and Steedman M.

"Extracting Common Sense Knowledge from Text for Robot Planning."

IEEE International Conference on Robotics and Automation (ICRA), (2014): 3749 – 56.


Kämpgen B, März K, Hafezi M, Adler A, Philipp P et al.

"Challenges in Collecting Patient Characteristics for Analysis using Linked Data."

13. Jahrestagung der Deutschen Gesellschaft für Computer- und Roboterassistierte Chirurgie (CURAC), (2014).

Katić D, Wekerle AL, Goertler J, Spengler P, Bodenstedt S et al.

“Context-aware Augmented Reality in laparoscopic surgery.”

Comp. Med. Imag. and Graph., 37, no. 2, (2013): 174 – 82.


Katić D, Wekerle AL, Gaertner F, Kenngott HG, Müller-Stich BP et al.

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

Proc. of Information Processing in Computer Assisted Interventions (IPCAI), (2014).


Katić D, Julliard C, Wekerle AL, Kenngott H, Müller-Stich BP et al.

“LapOntoSPM - An Ontology for Laparoscopic Surgeries and its Application to Surgical Phase Recognition.”

Int J CARS (2015).


Philipp P, Maleshkova M, Katic D, Weber C, Götz M et al.

“Towards Cognitive Pipelines of Medical Assistance Algorithms.”,

Int J CARS (to appear).

Rettinger A, Schumilin A, Thoma S, and Ell B.

“Learning a Cross-Lingual Semantic Representation of Relations Expressed in Text.”

Proc. of the 12th Extended Semantic Web Confer-ence (ESWC 2015): 337-52.

Schoch NJ, Philipp P, Weller T, Engelhardt S, Volovyk M et al.

"Cognitive tools pipeline for assistance of mitral valve surgery."

SPIE Medical Imaging (2016) (accepted).

Staab S, Schnurr H-P, Studer R, Sure Y.

„Knowledge Processes and Ontologies."

In: IEEE Intelligent Systems 16(1): 26-34 (2001)