Novel experimental and software methods for image reconstruction and localization in capsule endoscopy
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 i...
| Main Authors: | , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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Georg Thieme Verlag KG
2018-02-01
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| Series: | Endoscopy International Open |
| Online Access: | http://www.thieme-connect.de/DOI/DOI?10.1055/s-0043-121882 |
| _version_ | 1819105932054888448 |
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| author | Anastasios Koulaouzidis Dimitris K. Iakovidis Diana E. Yung Evangelos Mazomenos Federico Bianchi Alexandros Karagyris George Dimas Danail Stoyanov Henrik Thorlacius Ervin Toth Gastone Ciuti |
| author_facet | Anastasios Koulaouzidis Dimitris K. Iakovidis Diana E. Yung Evangelos Mazomenos Federico Bianchi Alexandros Karagyris George Dimas Danail Stoyanov Henrik Thorlacius Ervin Toth Gastone Ciuti |
| author_sort | Anastasios Koulaouzidis |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-12-22T02:30:06Z |
| format | Article |
| id | doaj.art-b83359ecb9624f47b17aa6e7efa1e86f |
| institution | Directory Open Access Journal |
| issn | 2364-3722 2196-9736 |
| language | English |
| last_indexed | 2024-12-22T02:30:06Z |
| publishDate | 2018-02-01 |
| publisher | Georg Thieme Verlag KG |
| record_format | Article |
| series | Endoscopy International Open |
| spelling | doaj.art-b83359ecb9624f47b17aa6e7efa1e86f2022-12-21T18:41:55ZengGeorg Thieme Verlag KGEndoscopy International Open2364-37222196-97362018-02-010602E205E21010.1055/s-0043-121882Novel experimental and software methods for image reconstruction and localization in capsule endoscopyAnastasios Koulaouzidis0Dimitris K. Iakovidis1Diana E. Yung2Evangelos Mazomenos3Federico Bianchi4Alexandros Karagyris5George Dimas6Danail Stoyanov7Henrik Thorlacius8Ervin Toth9Gastone Ciuti10Centre for Liver & Digestive Disorders, The Royal Infirmary of Edinburgh, Edinburgh, UKUniversity of Thessaly, Department of Computer Science and Biomedical Informatics, Lamia, GreeceCentre for Liver & Digestive Disorders, The Royal Infirmary of Edinburgh, Edinburgh, UKCentre of Medical Image Computing and Department of Computer Science, University College London, London, UKThe BioRobotics Institute, Scuola Superiore Sant’Anna, Pisa, ItalyIBM Research, Almaden California, United StatesUniversity of Thessaly, Department of Computer Science and Biomedical Informatics, Lamia, GreeceCentre of Medical Image Computing and Department of Computer Science, University College London, London, UKDepartment of Clinical Sciences, Lund University, Malmö, SwedenDepartment of Gastroenterology, Skåne University Hospital, Malmö, SwedenThe BioRobotics Institute, Scuola Superiore Sant’Anna, Pisa, ItalyBackground 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.http://www.thieme-connect.de/DOI/DOI?10.1055/s-0043-121882 |
| spellingShingle | Anastasios Koulaouzidis Dimitris K. Iakovidis Diana E. Yung Evangelos Mazomenos Federico Bianchi Alexandros Karagyris George Dimas Danail Stoyanov Henrik Thorlacius Ervin Toth Gastone Ciuti Novel experimental and software methods for image reconstruction and localization in capsule endoscopy Endoscopy International Open |
| title | Novel experimental and software methods for image reconstruction and localization in capsule endoscopy |
| title_full | Novel experimental and software methods for image reconstruction and localization in capsule endoscopy |
| title_fullStr | Novel experimental and software methods for image reconstruction and localization in capsule endoscopy |
| title_full_unstemmed | Novel experimental and software methods for image reconstruction and localization in capsule endoscopy |
| title_short | Novel experimental and software methods for image reconstruction and localization in capsule endoscopy |
| title_sort | novel experimental and software methods for image reconstruction and localization in capsule endoscopy |
| url | http://www.thieme-connect.de/DOI/DOI?10.1055/s-0043-121882 |
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