Project description
Medical endoscopes may soon get the green light for augmented reality and autonomous navigation
Mapping of regions of importance is fundamental to interact with the environment, from satellite maps of glaciers to functional maps for GPS navigators. Autonomous vehicles also work by matching visual data to an existing map which needs to be constantly updated and extended. Now, EndoMapper is developing a similar mapping system to support endoscopic procedures like colonoscopy, tumour biopsy, or even targeted drug delivery. To accomplish their world-first, the team must tackle the challenge of modelling non-rigidity. Unlike roads and byways, the body's tissues and organs are prone to change as the endoscope moves. Taking advantage of new non-rigid mathematical models and machine learning, endoscopy may soon enter the realm of augmented virtual reality and autonomous navigation.
Fields of science
- natural sciencesearth and related environmental sciencesphysical geographycartography
- natural sciencescomputer and information sciencesartificial intelligencemachine learningdeep learning
- natural sciencesmathematicspure mathematicsgeometry
- natural sciencescomputer and information sciencessoftwaresoftware applicationssimulation software
- natural sciencesmathematicsapplied mathematicsmathematical model
Programme(s)
Funding Scheme
RIA - Research and Innovation actionCoordinator
50009 Zaragoza
Spain
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Participants (3)
63000 Clermont Ferrand
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W1W 7TS London
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
WC1E 6BT London
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