international • research • cooperation
International Network for Capsule Imaging in Endoscopy
Wireless capsule endoscopy
CapsNetwork
Our intestine can reveal a lot of information about our general health. With a small camera the patient can swallow and the help of artificial intelligence, the medical practitioners can take better and more informed decisions when diagnosing different diseases like Crohn’s disease, inflammatory bowel disease, or cancer. In CapsNetwork, six research institutions join their effort to increase the understanding of cancer detection using Wireless Capsule endoscopy

IMAGES FROM
INSIDE AN INTESTINE



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LATEST NEWS OF CAPSNETWORK
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CAPS Network at CVIP 2026
The 11th International Conference on Computer Vision and Image Processing (CVIP 2026) will take place on 9–12 December 2026 at the National Institute of Technology Calicut (NIT Calicut), India. The conference is jointly organised by NIT Calicut and the Norwegian University of Science and Technology (NTNU). CVIP 2026 brings together researchers, academics, and industry professionals…
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New EU-funded Doctoral Network: CAPTURE
We are pleased to announce that CAPTURE – Improved Diagnosis, Monitoring and Treatment through European Doctoral Collaboration in Capsule Endoscopy – has been awarded funding through the European Union’s Marie Skłodowska-Curie Actions (MSCA) Doctoral Networks programme. Coordinated by NTNU, the four-year project will bring together researchers and institutions across Europe to advance wireless capsule endoscopy…
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CapsNetwork and CapsTrain workshop at CVCS 2026
On 22 September 2026, CapsNetwork and CapsTrain hosted a joint workshop as part of the Colour and Visual Computing Symposium (CVCS 2026) in Gjøvik, Norway. The workshop brought together researchers working within wireless capsule endoscopy (WCE), medical imaging and artificial intelligence. The programme covered recent developments in WCE and related medical imaging topics, including AI-based…
six universities. three continents.
Meet our project partners
CapsNetwork is funded by

The Norwegian Research Council (project number 322600)





