Learning Dynamic Spatial Relations: The Case of a Knowledge-based Endoscopic Camera Guidance Robot

✍ Scribed by Andreas Bihlmaier (auth.)

Publisher: Springer Vieweg
Year: 2016
Tongue: English
Leaves: 278
Edition: 1
Category: Library

No coin nor oath required. For personal study only.

✦ Synopsis

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.

✦ Table of Contents

Front Matter....Pages I-XV
Introduction....Pages 1-22
Endoscope Robots and Automated Camera Guidance....Pages 23-102
System Architecture and Conceptual Overview....Pages 103-125
Modular Research Platform for Robot-Assisted Minimally-Invasive Surgery....Pages 127-155
Learning of Surgical Know-How by Models of Spatial Relations....Pages 157-184
Intraoperative Robot-Based Camera Assistance....Pages 185-208
Evaluation Studies....Pages 209-218
Conclusion....Pages 219-222
Back Matter....Pages 223-267

✦ Subjects

Artificial Intelligence (incl. Robotics);Minimally Invasive Surgery;Pattern Recognition

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