Recognition of risk situations based on endoscopic instrument tracking and knowledge based situation modeling

Stefanie Speidel; Gunther Sudra; Julien Senemaud; Maximilian Drentschew; Beat Peter Müller-Stich; Carsten Gutt; Rüdiger Dillmann

doi:10.1117/12.770385

17 March 2008 Recognition of risk situations based on endoscopic instrument tracking and knowledge based situation modeling

Stefanie Speidel, Gunther Sudra, Julien Senemaud, Maximilian Drentschew, Beat Peter Müller-Stich, Carsten Gutt, Rüdiger Dillmann

Author Affiliations +

Proceedings Volume 6918, Medical Imaging 2008: Visualization, Image-Guided Procedures, and Modeling; 69180X (2008) https://doi.org/10.1117/12.770385
Event: Medical Imaging, 2008, San Diego, California, United States

Abstract

Minimally invasive surgery has gained significantly in importance over the last decade due to the numerous advantages on patient-side. The surgeon has to adapt special operation-techniques and deal with difficulties like the complex hand-eye coordination, limited field of view and restricted mobility. To alleviate these constraints we propose to enhance the surgeon's capabilities by providing a context-aware assistance using augmented reality (AR) techniques. In order to generate a context-aware assistance it is necessary to recognize the current state of the intervention using intraoperatively gained sensor data and a model of the surgical intervention. In this paper we present the recognition of risk situations, the system warns the surgeon if an instrument gets too close to a risk structure. The context-aware assistance system starts with an image-based analysis to retrieve information from the endoscopic images. This information is classified and a semantic description is generated. The description is used to recognize the current state and launch an appropriate AR visualization. In detail we present an automatic vision-based instrument tracking to obtain the positions of the instruments. Situation recognition is performed using a knowledge representation based on a description logic system. Two augmented reality visualization programs are realized to warn the surgeon if a risk situation occurs.

Citation Download Citation

Stefanie Speidel, Gunther Sudra, Julien Senemaud, Maximilian Drentschew, Beat Peter Müller-Stich, Carsten Gutt, and Rüdiger Dillmann "Recognition of risk situations based on endoscopic instrument tracking and knowledge based situation modeling", Proc. SPIE 6918, Medical Imaging 2008: Visualization, Image-Guided Procedures, and Modeling, 69180X (17 March 2008); https://doi.org/10.1117/12.770385

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available