| 1. |
- Iakovidis, Dimitris K., et al.
(författare)
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Robotic validation of visual odometry for wireless capsule endoscopy
- 2016
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Ingår i: IST 2016 - 2016 IEEE International Conference on Imaging Systems and Techniques, Proceedings. - 9781509018178 ; , s. 83-87
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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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| 2. |
- Koulaouzidis, Anastasios, et al.
(författare)
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KID Project : an internet-based digital video atlas of capsule endoscopy for research purposes
- 2017
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Ingår i: Endoscopy International Open. - : Georg Thieme Verlag KG. - 2364-3722 .- 2196-9736. ; 5:6, s. 477-483
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND AND AIMS: Capsule endoscopy (CE) has revolutionized small-bowel (SB) investigation. Computational methods can enhance diagnostic yield (DY); however, incorporating machine learning algorithms (MLAs) into CE reading is difficult as large amounts of image annotations are required for training. Current databases lack graphic annotations of pathologies and cannot be used. A novel database, KID, aims to provide a reference for research and development of medical decision support systems (MDSS) for CE.METHODS: Open-source software was used for the KID database. Clinicians contribute anonymized, annotated CE images and videos. Graphic annotations are supported by an open-access annotation tool (Ratsnake). We detail an experiment based on the KID database, examining differences in SB lesion measurement between human readers and a MLA. The Jaccard Index (JI) was used to evaluate similarity between annotations by the MLA and human readers.RESULTS: The MLA performed best in measuring lymphangiectasias with a JI of 81 ± 6 %. The other lesion types were: angioectasias (JI 64 ± 11 %), aphthae (JI 64 ± 8 %), chylous cysts (JI 70 ± 14 %), polypoid lesions (JI 75 ± 21 %), and ulcers (JI 56 ± 9 %).CONCLUSION: MLA can perform as well as human readers in the measurement of SB angioectasias in white light (WL). Automated lesion measurement is therefore feasible. KID is currently the only open-source CE database developed specifically to aid development of MDSS. Our experiment demonstrates this potential.
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| 3. |
- Koulaouzidis, Anastasios, et al.
(författare)
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Novel experimental and software methods for image reconstruction and localization in capsule endoscopy
- 2018
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Ingår i: Endoscopy International Open. - : Georg Thieme Verlag KG. - 2364-3722 .- 2196-9736. ; 6:2, s. 205-210
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Tidskriftsartikel (refereegranskat)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 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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| 4. |
- Vasilakakis, Michael, et al.
(författare)
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Follow-up on: optimizing lesion detection in small bowel capsule endoscopy and beyond: from present problems to future solutions
- 2019
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Ingår i: Expert Review of Gastroenterology and Hepatology. - : Informa UK Limited. - 1747-4124 .- 1747-4132. ; 13:2, s. 129-141
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Tidskriftsartikel (refereegranskat)abstract
- Introduction: This review presents noteworthy advances in clinical and experimental Capsule Endoscopy (CE), focusing on the progress that has been reported over the last 5 years since our previous review on the subject. Areas covered: This study presents the commercially available CE platforms, as well as the advances made in optimizing the diagnostic capabilities of CE. The latter includes recent concept and prototype capsule endoscopes, medical approaches to improve diagnostic yield, and progress in software for enhancing visualization, abnormality detection, and lesion localization. Expert commentary: Currently, moving through the second decade of CE evolution, there are still several open issues and remarkable challenges to overcome.
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