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Novel experimental and software methods for image reconstruction and localization in capsule endoscopy

Koulaouzidis, Anastasios LU ; Iakovidis, Dimitris K ; Yung, Diana E ; Mazomenos, Evangelos ; Bianchi, Federico ; Karagyris, Alexandros ; Dimas, George ; Stoyanov, Danail ; Thorlacius, Henrik LU and Toth, Ervin LU , et al. (2018) In Endoscopy International Open 6(2). p.205-210
Abstract

Background and study aims : Capsule endoscopy (CE) is invaluable for minimally invasive endoscopy of the gastrointestinal tract; however, several technological limitations remain including lack of reliable lesion localization. We present an approach to 3D reconstruction and localization using visual information from 2D CE images.

Patients and methods : Colored thumbtacks were secured in rows to the internal wall of a LifeLike bowel model. A PillCam SB3 was calibrated and navigated linearly through the lumen by a high-precision robotic arm. The motion estimation algorithm used data (light falling on the object, fraction of reflected light and surface geometry) from 2D CE images in the video sequence to achieve 3D reconstruction of... (More)

Background and study aims : Capsule endoscopy (CE) is invaluable for minimally invasive endoscopy of the gastrointestinal tract; however, several technological limitations remain including lack of reliable lesion localization. We present an approach to 3D reconstruction and localization using visual information from 2D CE images.

Patients and methods : Colored thumbtacks were secured in rows to the internal wall of a LifeLike bowel model. A PillCam SB3 was calibrated and navigated linearly through the lumen by a high-precision robotic arm. The motion estimation algorithm used data (light falling on the object, fraction of reflected light and surface geometry) from 2D CE images in the video sequence to achieve 3D reconstruction of the bowel model at various frames. The ORB-SLAM technique was used for 3D reconstruction and CE localization within the reconstructed model. This algorithm compared pairs of points between images for reconstruction and localization.

Results:  As the capsule moved through the model bowel 42 to 66 video frames were obtained per pass. Mean absolute error in the estimated distance travelled by the CE was 4.1 ± 3.9 cm. Our algorithm was able to reconstruct the cylindrical shape of the model bowel with details of the attached thumbtacks. ORB-SLAM successfully reconstructed the bowel wall from simultaneous frames of the CE video. The "track" in the reconstruction corresponded well with the linear forwards-backwards movement of the capsule through the model lumen.

Conclusion:  The reconstruction methods, detailed above, were able to achieve good quality reconstruction of the bowel model and localization of the capsule trajectory using information from the CE video and images alone.

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organization
publishing date
type
Contribution to journal
publication status
published
subject
in
Endoscopy International Open
volume
6
issue
2
pages
205 - 210
publisher
Georg Thieme Verlag
external identifiers
  • pmid:29399619
ISSN
2364-3722
DOI
10.1055/s-0043-121882
language
English
LU publication?
yes
id
ed67e2fa-2591-4d02-be94-df0099e5fb03
date added to LUP
2020-05-15 16:03:09
date last changed
2020-05-15 16:03:09
@article{ed67e2fa-2591-4d02-be94-df0099e5fb03,
  abstract     = {{<p>Background and study aims : Capsule endoscopy (CE) is invaluable for minimally invasive endoscopy of the gastrointestinal tract; however, several technological limitations remain including lack of reliable lesion localization. We present an approach to 3D reconstruction and localization using visual information from 2D CE images.</p><p>Patients and methods : Colored thumbtacks were secured in rows to the internal wall of a LifeLike bowel model. A PillCam SB3 was calibrated and navigated linearly through the lumen by a high-precision robotic arm. The motion estimation algorithm used data (light falling on the object, fraction of reflected light and surface geometry) from 2D CE images in the video sequence to achieve 3D reconstruction of the bowel model at various frames. The ORB-SLAM technique was used for 3D reconstruction and CE localization within the reconstructed model. This algorithm compared pairs of points between images for reconstruction and localization.</p><p>Results:  As the capsule moved through the model bowel 42 to 66 video frames were obtained per pass. Mean absolute error in the estimated distance travelled by the CE was 4.1 ± 3.9 cm. Our algorithm was able to reconstruct the cylindrical shape of the model bowel with details of the attached thumbtacks. ORB-SLAM successfully reconstructed the bowel wall from simultaneous frames of the CE video. The "track" in the reconstruction corresponded well with the linear forwards-backwards movement of the capsule through the model lumen.</p><p>Conclusion:  The reconstruction methods, detailed above, were able to achieve good quality reconstruction of the bowel model and localization of the capsule trajectory using information from the CE video and images alone.</p>}},
  author       = {{Koulaouzidis, Anastasios and Iakovidis, Dimitris K and Yung, Diana E and Mazomenos, Evangelos and Bianchi, Federico and Karagyris, Alexandros and Dimas, George and Stoyanov, Danail and Thorlacius, Henrik and Toth, Ervin and Ciuti, Gastone}},
  issn         = {{2364-3722}},
  language     = {{eng}},
  number       = {{2}},
  pages        = {{205--210}},
  publisher    = {{Georg Thieme Verlag}},
  series       = {{Endoscopy International Open}},
  title        = {{Novel experimental and software methods for image reconstruction and localization in capsule endoscopy}},
  url          = {{http://dx.doi.org/10.1055/s-0043-121882}},
  doi          = {{10.1055/s-0043-121882}},
  volume       = {{6}},
  year         = {{2018}},
}