ArticleDiagnostics (Basel, Switzerland)2021
Feature Point Tracking-Based Localization of Colon Capsule Endoscope.
Article in Diagnostics (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed.
- Artificial Intelligence in Gastrointestinal Wireless Capsule Endoscopy: A Systematic Literature Review and Meta-Analysis.Diagnostics (Basel, Switzerland) · 2026Review
- Expected Values of Artificial Intelligence in Colon Capsule Endoscopy: Artificial Intelligence in Capsule Endoscopy Consortium Position Statement.Endoscopy international open · 2026Article
- Towards full integration of explainable artificial intelligence in colon capsule endoscopy's pathway.Scientific reports · 2025Article
- Localization of Capsule Endoscope in Alimentary Tract by Computer-Aided Analysis of Endoscopic Images.Sensors (Basel, Switzerland) · 2025Article
- Recent Advancements in Localization Technologies for Wireless Capsule Endoscopy: A Technical Review.Sensors (Basel, Switzerland) · 2025Review
- Pose estimation via structure-depth information from monocular endoscopy images sequence.Biomedical optics express · 2024Article
- Interobserver agreement on landmark and flexure identification in colon capsule endoscopy.Techniques in coloproctology · 2023Article
- Artificial Intelligence in Colon Capsule Endoscopy-A Systematic Review.Diagnostics (Basel, Switzerland) · 2022Review
- Edge artificial intelligence wireless video capsule endoscopy.Scientific reports · 2022Article
- Wireless Capsule Endoscope Localization with Phase Detection Algorithm and Adaptive Body Model.Sensors (Basel, Switzerland) · 2022Article
- Examination of Entire Gastrointestinal Tract: A Perspective of Mouth to Anus (M2A) Capsule Endoscopy.Diagnostics (Basel, Switzerland) · 2021Review
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In large bowel investigations using endoscopic capsules and upon detection of significant findings, physicians require the location of those findings for a follow-up therapeutic colonoscopy. To cater to this need, we propose a model based on tracking feature points in consecutive frames of videos retrieved from colon capsule endoscopy investigations. By locally approximating the colon as a cylinder, we obtained both the displacement and the orientation of the capsule using geometrical assumptions and by setting priors on both physical properties of the intestine and the image sample frequency of the endoscopic capsule. Our proposed model tracks a colon capsule endoscope through the large intestine for different prior selections. A discussion on validating the findings in terms of intra and inter capsule and expert panel validation is provided. The performance of the model is evaluated based on the average difference in multiple reconstructed capsule's paths through the large intestine. The path difference averaged over all videos was as low as 4±0.7 cm, with min and max error corresponding to 1.2 and 6.0 cm, respectively. The inter comparison addresses frame classification for the rectum, descending and sigmoid, splenic flexure, transverse, hepatic, and ascending, with an average accuracy of 86%.
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