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 Contact CV		PD Dr. med. Arianeb Mehrabi Contact CV		Prof. Dr. rer. nat. Rudi Studer Contact CV

Our Team

v.l.n.r.: Prof. Y. Sure-Vetter (Nachfolge Prof. Studer), Dr. M. Maleshkova (Nachwuchsgruppenleiterin Informatik), Dr. A. Rettinger (Nachwuchsgruppenleiter Informatik), S. Thoma (Doktorand Informatik), Dr. D. Katic (Postdoktorand Informatik), P. Philipp (Doktorand Informatik), T. Weller (Informatik), Prof. R. Studer (Projektleiter Informatik)

Publications

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.

doi:10.1109/ICRA.2014.6907402.

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.

doi:10.1016/j.compmedimag.2013.03.003.

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).

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

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).

doi:10.1007/s11548-015-1222-1.

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)