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Towards automated visual flexible endoscope navigation
Nanda van der Stap1, Ferdinand van der Heijden, Ivo A M J Broeders
1Robotics and Minimally Invasive Surgery Group, MIRA Institute for Biomedical Technology and Technical Medicine, Carré 3.623, University of Twente, Drienerlolaan 5, 7500, AE, Enschede, The Netherlands, n.stap@utwente.nl.
Background:
The design of flexible endoscopes has not changed significantly in the past 50 years. A trend is observed towards a wider application of flexible endoscopes with an increasing role in complex intraluminal therapeutic procedures. The nonintuitive and nonergonomical steering mechanism now forms a barrier in the extension of flexible endoscope applications. Automating the navigation of endoscopes could be a solution for this problem. This paper summarizes the current state of the art in image-based navigation algorithms. The objectives are to find the most promising navigation system(s) to date and to indicate fields for further research.
Methods:
A systematic literature search was performed using three general search terms in two medical-technological literature databases. Papers were included according to the inclusion criteria. A total of 135 papers were analyzed. Ultimately, 26 were included.
Results:
Navigation often is based on visual information, which means steering the endoscope using the images that the endoscope produces. Two main techniques are described: lumen centralization and visual odometry. Although the research results are promising, no successful, commercially available automated flexible endoscopy system exists to date.
Conclusions:
Automated systems that employ conventional flexible endoscopes show the most promising prospects in terms of cost and applicability. To produce such a system, the research focus should lie on finding low-cost mechatronics and technologically robust steering algorithms. Additional functionality and increased efficiency can be obtained through software development. The first priority is to find real-time, robust steering algorithms. These algorithms need to handle bubbles, motion blur, and other image artifacts without disrupting the steering process.
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