Edge artificial intelligence wireless video capsule endoscopy

A. Sahafi, Y. Wang, C. L.M. Rasmussen, P. Bollen, G. Baatrup, V. Blanes-Vidal, J. Herp, E. S. Nadimi*


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Gastrointestinal (GI) tract diseases are responsible for substantial morbidity and mortality worldwide, including colorectal cancer, which has shown a rising incidence among adults younger than 50. Although this could be alleviated by regular screening, only a small percentage of those at risk are screened comprehensively, due to shortcomings in accuracy and patient acceptance. To address these challenges, we designed an artificial intelligence (AI)-empowered wireless video endoscopic capsule that surpasses the performance of the existing solutions by featuring, among others: (1) real-time image processing using onboard deep neural networks (DNN), (2) enhanced visualization of the mucous layer by deploying both white-light and narrow-band imaging, (3) on-the-go task modification and DNN update using over-the-air-programming and (4) bi-directional communication with patient’s personal electronic devices to report important findings. We tested our solution in an in vivo setting, by administrating our endoscopic capsule to a pig under general anesthesia. All novel features, successfully implemented on a single platform, were validated. Our study lays the groundwork for clinically implementing a new generation of endoscopic capsules, which will significantly improve early diagnosis of upper and lower GI tract diseases.

TidsskriftScientific Reports
Udgave nummer1
Antal sider10
StatusUdgivet - 2022

Bibliografisk note

Funding Information:
This research was financially supported in part by a research grant from Louis-Hansen fund (Grant 74400), the University of Southern Denmark and Odense University Hospital through the Project, “EFFICACY”.

Publisher Copyright:
© 2022, The Author(s).


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