Share Email Print
cover

Proceedings Paper

Automatic classification of minimally invasive instruments based on endoscopic image sequences
Author(s): Stefanie Speidel; Julia Benzko; Sebastian Krappe; Gunther Sudra; Pedram Azad; Beat Peter Müller-Stich; Carsten Gutt; Rüdiger Dillmann
Format Member Price Non-Member Price
PDF $14.40 $18.00

Paper Abstract

Minimally invasive surgery is nowadays a frequently applied technique and can be regarded as a major breakthrough in surgery. The surgeon has to adopt special operation-techniques and deal with difficulties like the complex hand-eye coordination and restricted mobility. To alleviate these constraints we propose to enhance the surgeon's capabilities by providing a context-aware assistance using augmented reality techniques. To analyze the current situation for context-aware assistance, we need intraoperatively gained sensor data and a model of the intervention. A situation consists of information about the performed activity, the used instruments, the surgical objects, the anatomical structures and defines the state of an intervention for a given moment in time. The endoscopic images provide a rich source of information which can be used for an image-based analysis. Different visual cues are observed in order to perform an image-based analysis with the objective to gain as much information as possible about the current situation. An important visual cue is the automatic recognition of the instruments which appear in the scene. In this paper we present the classification of minimally invasive instruments using the endoscopic images. The instruments are not modified by markers. The system segments the instruments in the current image and recognizes the instrument type based on three-dimensional instrument models.

Paper Details

Date Published: 13 March 2009
PDF: 8 pages
Proc. SPIE 7261, Medical Imaging 2009: Visualization, Image-Guided Procedures, and Modeling, 72610A (13 March 2009); doi: 10.1117/12.811112
Show Author Affiliations
Stefanie Speidel, ITEC Univ. Karlsruhe (Germany)
Julia Benzko, ITEC Univ. Karlsruhe (Germany)
Sebastian Krappe, ITEC Univ. Karlsruhe (Germany)
Gunther Sudra, ITEC Univ. Karlsruhe (Germany)
Pedram Azad, ITEC Univ. Karlsruhe (Germany)
Beat Peter Müller-Stich, Univ. of Heidelberg (Germany)
Carsten Gutt, Univ. of Heidelberg (Germany)
Rüdiger Dillmann, ITEC Univ. Karlsruhe (Germany)


Published in SPIE Proceedings Vol. 7261:
Medical Imaging 2009: Visualization, Image-Guided Procedures, and Modeling
Michael I. Miga; Kenneth H. Wong, Editor(s)

© SPIE. Terms of Use
Back to Top