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Sinopsis
Andreas Bihlmaier describes a novel method to model dynamic spatial relations by machine learning techniques. The method is applied to the task of representing the tacit knowledge of a trained camera assistant in minimally-invasive surgery. The model is then used for intraoperative control of a robot that autonomously positions the endoscope. Furthermore, a modular robotics platform is described, which forms the basis for this knowledge-based assistance system. Promising results from a complex phantom study are presented.
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Acerca del autor
Andreas Bihlmaier is leader of the Cognitive Medical Technologies group in the Institute for Anthropomatics and Robotics – Intelligent Process Control and Robotics Lab (IAR-IPR) at the Karlsruhe Institute of Technology (KIT). His research focuses on cognitive surgical robotics for minimally-invasive surgery, as part of the SFB/Transregio 125 “Cognition-Guided Surgery”.
De la contraportada
Andreas Bihlmaier describes a novel method to model dynamic spatial relations by machine learning techniques. The method is applied to the task of representing the tacit knowledge of a trained camera assistant in minimally-invasive surgery. The model is then used for intraoperative control of a robot that autonomously positions the endoscope. Furthermore, a modular robotics platform is described, which forms the basis for this knowledge-based assistance system. Promising results from a complex phantom study are presented.
Contents
- Endoscope Robots and Automated Camera Guidance
- Knowledge-based Cognitive Systems
- Modular Research Platform for Robot-Assisted Surgery based on ROS
- Learning of Surgical Know-how by Models of Spatial Relations
- Intraoperative Camera Assistance
- Evaluation Study: TME in the Open Source Heidelberg Laparoscopic Phantom (OpenHELP)
- Scientists and students in the field of robotics, surgical assistance systems, cognitive and knowledge-based systems
- Practitioners in companies selling manually controlled robots or motorized endoscope holders
About the Author
Andreas Bihlmaier is leader of the Cognitive Medical Technologies group in the Institute for Anthropomatics and Robotics – Intelligent Process Control and Robotics Lab (IAR-IPR) at the Karlsruhe Institute of Technology (KIT). His research focuses on cognitive surgical robotics for minimally-invasive surgery, as part of the SFB/Transregio 125 “Cognition-Guided Surgery”.
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Learning Dynamic Spatial Relations
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Springer Fachmedien Wiesbaden Aug 2016, 2016
ISBN 10: 3658149132
ISBN 13: 9783658149130
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Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Andreas Bihlmaier describes a novel method to model dynamic spatial relations by machine learning techniques. The method is applied to the task of representing the tacit knowledge of a trained camera assistant in minimally-invasive surgery. The model is then used for intraoperative control of a robot that autonomously positions the endoscope. Furthermore, a modular robotics platform is described, which forms the basis for this knowledge-based assistance system. Promising results from a complex phantom study are presented. 284 pp. Englisch. Nº de ref. del artículo: 9783658149130
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Learning Dynamic Spatial Relations : The Case of a Knowledge-based Endoscopic Camera Guidance Robot
Publicado por
Springer Fachmedien Wiesbaden, 2016
ISBN 10: 3658149132
ISBN 13: 9783658149130
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Taschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - Andreas Bihlmaier describes a novel method to model dynamic spatial relations by machine learning techniques. The method is applied to the task of representing the tacit knowledge of a trained camera assistant in minimally-invasive surgery. The model is then used for intraoperative control of a robot that autonomously positions the endoscope. Furthermore, a modular robotics platform is described, which forms the basis for this knowledge-based assistance system. Promising results from a complex phantom study are presented. Nº de ref. del artículo: 9783658149130
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Learning Dynamic Spatial Relations: The Case of a Knowledge-based Endoscopic Camera Guidance Robot
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Learning Dynamic Spatial Relations
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ISBN 10: 3658149132
ISBN 13: 9783658149130
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Kartoniert / Broschiert. Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Publication in the field of technical sciencesEndoscope Robots and Automated Camera Guidance.- Knowledge-based Cognitive Systems.- Modular Research Platform for Robot-Assisted Surgery based on ROS.- Learning of Surgical Know-how by. Nº de ref. del artículo: 123075822
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Learning Dynamic Spatial Relations : The Case of a Knowledge-based Endoscopic Camera Guidance Robot
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Learning Dynamic Spatial Relations: The Case of a Knowledge-based Endoscopic Camera Guidance Robot
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Learning Dynamic Spatial Relations: The Case of a Knowledge-based Endoscopic Camera Guidance Robot
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Learning Dynamic Spatial Relations
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ISBN 10: 3658149132
ISBN 13: 9783658149130
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Taschenbuch. Condición: Neu. Neuware -Andreas Bihlmaier describes a novel method to model dynamic spatial relations by machine learning techniques. The method is applied to the task of representing the tacit knowledge of a trained camera assistant in minimally-invasive surgery. The model is then used for intraoperative control of a robot that autonomously positions the endoscope. Furthermore, a modular robotics platform is described, which forms the basis for this knowledge-based assistance system. Promising results from a complex phantom study are presented.Springer Vieweg in Springer Science + Business Media, Abraham-Lincoln-Straße 46, 65189 Wiesbaden 284 pp. Englisch. Nº de ref. del artículo: 9783658149130
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Learning Dynamic Spatial Relations: The Case of a Knowledge-based Endoscopic Camera Guidance Robot
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Condición: New. Print on Demand pp. 282. Nº de ref. del artículo: 385760305
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