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Sökning: WFRF:(Toth Ervin) > Konferensbidrag

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2.
  • Iakovidis, Dimitris K., et al. (författare)
  • Robotic validation of visual odometry for wireless capsule endoscopy
  • 2016
  • Ingår i: IST 2016 - 2016 IEEE International Conference on Imaging Systems and Techniques, Proceedings. - 9781509018178 ; , s. 83-87
  • Konferensbidrag (refereegranskat)abstract
    • Wireless capsule endoscopy (WCE) is the prime diagnostic modality for the small-bowel. It consists in a swallowable color camera that enables the visual detection and assessment of abnormalities, without patient discomfort. The localization of the capsule is currently performed in the 3D abdominal space using radiofrequency (RF) triangulation. However, this approach does not provide sufficient information for the localization of the capsule, and therefore for the localization of the detected abnormalities, within the gastrointestinal (GI) lumen. To cope with this problem, we have recently proposed a method for visual tracking of the capsule endoscope (CE). It is based solely on visual features extracted from the captured images during the journey of the CE in the GI tract, enabling therefore visual odometry. Due to lack of ex-vivo or in-vivo ground truth data, the feasibility of that method was assessed using relative measurements in an image-based simulation experiment. In this paper, we make one step forward towards the assessment of the absolute localization capabilities of visual odometry using a calibrated in-vitro experimental setup. The obtained results validate the feasibility of the proposed approach, highlight the difficulty of this complex problem, and reveal the challenges ahead.
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3.
  • Rukundo, Olivier, et al. (författare)
  • Tinted Capsule Endoscopy
  • 2018
  • Ingår i: Endoscopy. - : Georg Thieme Verlag KG. - 1438-8812. ; 50:4, s. 1-1
  • Konferensbidrag (refereegranskat)abstract
    • Unlike virtual chromoendoscopy-assisted capsule endoscopy, “tinted capsule endoscopy” aims at using a tinted optical dome and/or LEDs in the effort to enhance the detection and characterization of pathologies in capsule endoscopy images.
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