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Automatic classification of minimally invasive instruments based on endoscopic image sequences

Speidel, S.; Benzko, J.; Krappe, S.; Sudra, G.; Azad, P.; Müller-Stich, B.P.; Gutt, C.; Dillmann, R.

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. ... mehr

Zugehörige Institution(en) am KIT Institut für Anthropomatik (IFA)
Publikationstyp Proceedingsbeitrag
Jahr 2009
Sprache Englisch
Identifikator ISBN: 978-0-8194-7514-5
KITopen-ID: 1000027059
Erschienen in Medical Imaging 2009: Image perception, observer performance, and technology assessment, Lake Buena Vista, Florida, United States, 11-12 February 2009. Ed.: S. Berkman
Verlag SPIE, Bellingham (Wash.)
Seiten Article ID 72610A
Serie Proceedings of SPIE ; 7261
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